隐私计算与数据要素

9951 条实体 · 最后更新 2026-10-16T09:46:24.481Z · cryptography and security / computer and information sciences / electrical engineering, electronic engineering, information engineering / blockchain / computer security / computer science / cloud computing / scalability / philosophy / neuromorphic computing / cell biology / information theory

• Reservoir computing approaches to recurrent neural network training
  openalex 2009 置信度 0.90 Neural Networks and Reservoir ComputingAdvanced Memory and Neural ComputingNeural Networks and Applications
• Reservoir Computing Properties of Neural Dynamics in Prefrontal Cortex
  openalex 2016 置信度 0.90 Neural Networks and Reservoir ComputingNeural dynamics and brain functionAdvanced Memory and Neural Computing
• A Learning Algorithm for Continually Running Fully Recurrent Neural Networks
  openalex 1989 置信度 0.90 Neural Networks and ApplicationsNeural Networks and Reservoir ComputingCognitive Science and Education Research
• Dual in-memory computing of matrix-vector multiplication for accelerating neural networks
  openalex 2024 置信度 0.90 Advanced Memory and Neural ComputingFerroelectric and Negative Capacitance DevicesNeuroscience and Neural Engineering
• NUTS-BSNN: A non-uniform time-step binarized spiking neural network with energy-efficient in-memory computing macro
  openalex 2023 置信度 0.90 Advanced Memory and Neural ComputingFerroelectric and Negative Capacitance DevicesNeural dynamics and brain function
• Emerging Iontronic Neural Devices for Neuromorphic Sensory Computing
  openalex 2023 置信度 0.90 Advanced Memory and Neural ComputingNeural Networks and Reservoir ComputingNeural dynamics and brain function
• Fault-Tolerance of Binarized and Stochastic Computing-based Neural Networks
  openalex 2021 置信度 0.90 Stochastic Gradient Optimization TechniquesNeural Networks and ApplicationsQuantum Computing Algorithms and Architecture
• Nanoparticle-based computing architecture for nanoparticle neural networks
  openalex 2020 置信度 0.90 Advanced biosensing and bioanalysis techniquesQuantum-Dot Cellular AutomataAdvanced Memory and Neural Computing
• De novo composite design based on machine learning algorithm
  openalex 2017 置信度 0.90 Machine Learning in Materials ScienceAdditive Manufacturing and 3D Printing TechnologiesManufacturing Process and Optimization
• Constructive algorithm for fully connected cascade feedforward neural networks
  openalex 2015 置信度 0.90 Neural Networks and ApplicationsMachine Learning and ELMAdvanced Sensor and Control Systems
• A Supervised Learning Algorithm for Multilayer Spiking Neural Networks Based on Temporal Coding Toward Energy-Efficient VLSI Processor Design
  openalex 2021 置信度 0.90 Advanced Memory and Neural ComputingNeural dynamics and brain functionFerroelectric and Negative Capacitance Devices
• DeepX: A Software Accelerator for Low-Power Deep Learning Inference on Mobile Devices
  openalex 2016 置信度 0.90 Context-Aware Activity Recognition SystemsIoT and Edge/Fog ComputingAdvanced Neural Network Applications
• The "Wake-Sleep" Algorithm for Unsupervised Neural Networks
  openalex 1995 置信度 0.90 Neural dynamics and brain functionNeural Networks and ApplicationsAdvanced Memory and Neural Computing
• Brain-computer interface paradigms and neural coding
  openalex 2024 置信度 0.90 EEG and Brain-Computer InterfacesNeuroscience and Neural EngineeringNeural dynamics and brain function
• ML-On-Rails: Safeguarding Machine Learning Models in Software Systems — A Case Study
  openalex 2024 置信度 0.90 Adversarial Robustness in Machine LearningSecurity and Verification in ComputingAdvanced Malware Detection Techniques
• Darwin: A neuromorphic hardware co-processor based on spiking neural networks
  openalex 2017 置信度 0.90 Advanced Memory and Neural ComputingNeural dynamics and brain functionNeural Networks and Reservoir Computing
• Spiking Neural Networks Hardware Implementations and Challenges
  openalex 2019 置信度 0.90 Advanced Memory and Neural ComputingNeural Networks and Reservoir ComputingFerroelectric and Negative Capacitance Devices
• Eyeriss v2: A Flexible Accelerator for Emerging Deep Neural Networks on Mobile Devices
  openalex 2019 置信度 0.90 Advanced Neural Network ApplicationsAdvanced Memory and Neural ComputingParallel Computing and Optimization Techniques
• Real-time ocular artifact suppression using recurrent neural network for electro-encephalogram based brain-computer interface
  openalex 2005 置信度 0.90 EEG and Brain-Computer InterfacesBlind Source Separation TechniquesNeuroscience and Neural Engineering
• A Survey of Machine Learning in Edge Computing: Techniques, Frameworks, Applications, Issues, and Research Directions
  openalex 2024 置信度 0.90 IoT and Edge/Fog ComputingData Stream Mining TechniquesAdvanced Neural Network Applications
• Enabling Communication for Locked-in Syndrome Patients using Deep Learning and an Emoji-based Brain Computer Interface
  openalex 2018 置信度 0.90 EEG and Brain-Computer InterfacesNeurobiology of Language and BilingualismNeurological disorders and treatments
• Computer‐Aided Diagnosis of Parkinson’s Disease Using Complex‐Valued Neural Networks and mRMR Feature Selection Algorithm
  openalex 2015 置信度 0.90 Voice and Speech DisordersMusic and Audio ProcessingSpeech and Audio Processing
• Computer-Aided Intracranial EEG Signal Identification Method Based on a Multi-Branch Deep Learning Fusion Model and Clinical Validation
  openalex 2021 置信度 0.90 EEG and Brain-Computer InterfacesFunctional Brain Connectivity StudiesEpilepsy research and treatment
• DANNA 2
  openalex 2018 置信度 0.90 Advanced Memory and Neural ComputingNeural Networks and Reservoir ComputingNeural Networks and Applications
• A flexible neural implant with ultrathin substrate for low-invasive brain–computer interface applications
  openalex 2022 置信度 0.90 Neuroscience and Neural EngineeringEEG and Brain-Computer InterfacesAdvanced Memory and Neural Computing
• Operant conditioning reflex implementation in a transparent Ta2O5–3x/Ta2O5−x homo-structured optoelectronic memristor for neuromorphic computing application
  openalex 2023 置信度 0.90 Advanced Memory and Neural ComputingNeural Networks and Reservoir ComputingNeural dynamics and brain function
• DNA sequences performs as natural language processing by exploiting deep learning algorithm for the identification of N4-methylcytosine
  openalex 2021 置信度 0.90 Epigenetics and DNA MethylationMachine Learning in BioinformaticsGenomics and Phylogenetic Studies
• Multi-objective optimization of multi-directional functionally graded beams using an effective deep feedforward neural network-SMPSO algorithm
  openalex 2021 置信度 0.90 Composite Structure Analysis and OptimizationTopology Optimization in EngineeringAdvanced machining processes and optimization
• Artificial Neural Networks to Assess Emotional States from Brain-Computer Interface
  openalex 2018 置信度 0.90 EEG and Brain-Computer InterfacesEmotion and Mood RecognitionNeural dynamics and brain function
• Machine learning modeling and genetic algorithm-based optimization of a novel pilot-scale thermosyphon-assisted falling film distillation unit
  openalex 2020 置信度 0.90 Innovative Microfluidic and Catalytic Techniques InnovationProcess Optimization and IntegrationHeat Transfer and Boiling Studies
• Combination of Organic‐Based Reservoir Computing and Spiking Neuromorphic Systems for a Robust and Efficient Pattern Classification
  openalex 2023 置信度 0.90 Advanced Memory and Neural ComputingNeural Networks and Reservoir ComputingNeural dynamics and brain function
• Investigation of steel frame damage based on computer vision and deep learning
  openalex 2021 置信度 0.90 Infrastructure Maintenance and MonitoringConcrete Corrosion and DurabilityNon-Destructive Testing Techniques
• Optimizing event-based neural networks on digital neuromorphic architecture: a comprehensive design space exploration
  openalex 2024 置信度 0.90 Advanced Memory and Neural ComputingFerroelectric and Negative Capacitance DevicesNeural Networks and Reservoir Computing
• Achieving supercomputer performane for neural net simulation with an array of digital signal processors
  openalex 1992 置信度 0.90 Neural Networks and ApplicationsAdvanced Memory and Neural ComputingNeural Networks and Reservoir Computing
• Graph neural network recommendation algorithm based on improved dual tower model
  openalex 2023 置信度 0.90 Recommender Systems and TechniquesAdvanced Graph Neural NetworksTopic Modeling
• Provable Advantages for Graph Algorithms in Spiking Neural Networks
  openalex 2021 置信度 0.90 Advanced Memory and Neural ComputingFerroelectric and Negative Capacitance DevicesNeural Networks and Reservoir Computing
• Affective Computing on Machine Learning-Based Emotion Recognition Using a Self-Made EEG Device
  openalex 2021 置信度 0.90 EEG and Brain-Computer InterfacesEmotion and Mood RecognitionNeural dynamics and brain function
• Research on Neural Network Hyper-Parameters Optimization Based on Firefly Algorithm
  openalex 2025 置信度 0.90 Advanced Sensor and Control SystemsAdvanced Algorithms and Applications
• DYNAP-SE2: a scalable multi-core dynamic neuromorphic asynchronous spiking neural network processor
  openalex 2024 置信度 0.90 Advanced Memory and Neural ComputingNeural Networks and Reservoir ComputingFerroelectric and Negative Capacitance Devices
• Deep reservoir computing: A critical experimental analysis
  openalex 2017 置信度 0.90 Neural Networks and Reservoir ComputingAdvanced Memory and Neural ComputingNeural dynamics and brain function
• Learning Nonlinear Dynamics in Efficient, Balanced Spiking Networks Using Local Plasticity Rules
  openalex 2018 置信度 0.90 Advanced Memory and Neural ComputingNeural dynamics and brain functionNeural Networks and Reservoir Computing
• Neural architecture search algorithm to optimize deep Transformer model for fault detection in electrical power distribution systems
  openalex 2023 置信度 0.90 Power Systems Fault DetectionPower Transformer Diagnostics and InsulationPower System Reliability and Maintenance
• Towards synthetic neural networks: can artificial electrochemical neurons be coupled with artificial memristive synapses?
  openalex 2020 置信度 0.90 Advanced Memory and Neural ComputingFerroelectric and Negative Capacitance DevicesNeural Networks and Reservoir Computing
• Loihi: A Neuromorphic Manycore Processor with On-Chip Learning
  openalex 2018 置信度 0.90 Advanced Memory and Neural ComputingNeural dynamics and brain functionFerroelectric and Negative Capacitance Devices
• Application of neural network and genetic algorithm in identification of a model of a variable mass underwater vehicle
  openalex 2015 置信度 0.90 Control Systems and IdentificationAdaptive Control of Nonlinear SystemsFault Detection and Control Systems
• Training Probabilistic Spiking Neural Networks with First- To-Spike Decoding
  openalex 2018 置信度 0.90 Advanced Memory and Neural ComputingNeural dynamics and brain functionNeural Networks and Reservoir Computing
• To Spike or Not to Spike: That Is the Question
  openalex 2015 置信度 0.90 Advanced Memory and Neural ComputingNeural dynamics and brain functionFerroelectric and Negative Capacitance Devices
• Amorphous InGaZnO (a-IGZO) Synaptic Transistor for Neuromorphic Computing
  openalex 2022 置信度 0.90 Advanced Memory and Neural ComputingNeural Networks and Reservoir ComputingFerroelectric and Negative Capacitance Devices
• Firefly algorithm based WSN-IoT security enhancement with machine learning for intrusion detection
  openalex 2024 置信度 0.90 Network Security and Intrusion DetectionAnomaly Detection Techniques and ApplicationsSmart Grid Security and Resilience
• Soft Computing-Based EEG Classification by Optimal Feature Selection and Neural Networks
  openalex 2019 置信度 0.90 EEG and Brain-Computer InterfacesBlind Source Separation TechniquesNeuroscience and Neural Engineering
• Ionic Diffusive Nanomemristors with Dendritic Competition and Cooperation Functions for Ultralow Voltage Neuromorphic Computing
  openalex 2024 置信度 0.90 Advanced Memory and Neural ComputingNeural dynamics and brain functionPhotoreceptor and optogenetics research
• Abisko: Deep codesign of an architecture for spiking neural networks using novel neuromorphic materials
  openalex 2023 置信度 0.90 Advanced Memory and Neural ComputingFerroelectric and Negative Capacitance DevicesCCD and CMOS Imaging Sensors
• A Graph Neural Network-Based Digital Twin for Network Slicing Management
  openalex 2020 置信度 0.90 Software-Defined Networks and 5GSoftware System Performance and ReliabilityAdvanced Computing and Algorithms
• Machine Learning for Fog Computing: Review, Opportunities and a Fog Application Classifier and Scheduler
  openalex 2022 置信度 0.90 IoT and Edge/Fog ComputingAir Quality Monitoring and ForecastingIoT Networks and Protocols
• Stroke risk study based on deep learning-based magnetic resonance imaging carotid plaque automatic segmentation algorithm
  openalex 2023 置信度 0.90 Cerebrovascular and Carotid Artery DiseasesCardiovascular Disease and AdiposityBrain Tumor Detection and Classification
• IoT-Based Intrusion Detection System Using New Hybrid Deep Learning Algorithm
  openalex 2024 置信度 0.90 Network Security and Intrusion DetectionInternet Traffic Analysis and Secure E-votingAnomaly Detection Techniques and Applications
• Interactive Supercomputing on 40,000 Cores for Machine Learning and Data Analysis
  openalex 2018 置信度 0.90 Cloud Computing and Resource ManagementParallel Computing and Optimization TechniquesAdvanced Data Storage Technologies
• Tunable Synaptic Characteristics of a Ti/TiO2/Si Memory Device for Reservoir Computing
  openalex 2021 置信度 0.90 Advanced Memory and Neural ComputingNeural Networks and Reservoir ComputingNeural dynamics and brain function
• Synaptic Properties and Short‐Term Memory Dynamics of TiO 2 /WO x Heterojunction Memristor for Reservoir Computing
  openalex 2024 置信度 0.90 Advanced Memory and Neural ComputingNeural Networks and Reservoir ComputingNeural dynamics and brain function
• Shenjing: A low power reconfigurable neuromorphic accelerator with partial-sum and spike networks-on-chip
  openalex 2020 置信度 0.90 Advanced Memory and Neural ComputingNeural Networks and Reservoir ComputingNeuroscience and Neural Engineering
• A memristor-based analogue reservoir computing system for real-time and power-efficient signal processing
  openalex 2022 置信度 0.90 Neural Networks and Reservoir ComputingAdvanced Memory and Neural ComputingNeural dynamics and brain function
• Self-Rectifying Memristor-Based Reservoir Computing for Real-Time Intrusion Detection in Cybersecurity
  openalex 2024 置信度 0.90 Neural Networks and Reservoir ComputingAdvanced Memory and Neural ComputingMachine Learning and ELM
• Optimization of pulsed ultrasonic‐assisted extraction of punicalagin from pomegranate ( Punica granatum ) peel: A comparison between response surface methodology and artificial neural network‐multiobjective genetic algorithm
  openalex 2020 置信度 0.90 Pomegranate: compositions and health benefitsPhytochemicals and Antioxidant ActivitiesNanocomposite Films for Food Packaging
• Using machine learning to estimate a key missing geochemical variable in mining exploration: Application of the Random Forest algorithm to multi-sensor core logging data
  openalex 2019 置信度 0.90 Geochemistry and Geologic MappingMineral Processing and GrindingHydrocarbon exploration and reservoir analysis
• Reservoir Computing
  openalex 2021 置信度 0.90 Neural Networks and Reservoir ComputingNeural Networks and ApplicationsAdvanced Memory and Neural Computing
• Fading memory echo state networks are universal
  openalex 2021 置信度 0.90 Neural Networks and Reservoir ComputingAdvanced Memory and Neural ComputingNeural Networks and Applications
• Multicenter Validation of a Deep Learning Detection Algorithm for Focal Cortical Dysplasia
  openalex 2021 置信度 0.90 Epilepsy research and treatmentFunctional Brain Connectivity StudiesEEG and Brain-Computer Interfaces
• Machine Learning Empowered Security Management and Quality of Service Provision in SDN-NFV Environment
  openalex 2021 置信度 0.90 Network Security and Intrusion DetectionSoftware-Defined Networks and 5GAdvanced Malware Detection Techniques
• Puma optimizer (PO): a novel metaheuristic optimization algorithm and its application in machine learning
  openalex 2024 置信度 0.90 Metaheuristic Optimization Algorithms ResearchAdvanced Multi-Objective Optimization AlgorithmsEvolutionary Algorithms and Applications
• Simple Reservoir Computing Capitalizing on the Nonlinear Response of Materials: Theory and Physical Implementations
  openalex 2021 置信度 0.90 Neural Networks and Reservoir ComputingAdvanced Memory and Neural ComputingNeural dynamics and brain function
• Braindrop: A Mixed-Signal Neuromorphic Architecture With a Dynamical Systems-Based Programming Model
  openalex 2018 置信度 0.90 Advanced Memory and Neural ComputingNeural Networks and Reservoir ComputingNeural dynamics and brain function
• Distributed Multiuser Computation Offloading for Cloudlet-Based Mobile Cloud Computing: A Game-Theoretic Machine Learning Approach
  openalex 2017 置信度 0.90 IoT and Edge/Fog ComputingPrivacy-Preserving Technologies in DataAge of Information Optimization
• A Deep Neural Collaborative Filtering Based Service Recommendation Method with Multi-Source Data for Smart Cloud-Edge Collaboration Applications
  openalex 2023 置信度 0.90 Recommender Systems and TechniquesCaching and Content DeliveryAdvanced Computing and Algorithms
• TinyVers: A Tiny Versatile System-on-Chip With State-Retentive eMRAM for ML Inference at the Extreme Edge
  openalex 2023 置信度 0.90 Advanced Memory and Neural ComputingParallel Computing and Optimization TechniquesCCD and CMOS Imaging Sensors
• Deep Learning for Computer Vision: A Brief Review
  openalex 2018 置信度 0.90 Advanced Neural Network ApplicationsVideo Surveillance and Tracking MethodsHuman Pose and Action Recognition
• Secure Deep Learning in Defense in Deep-Learning-as-a-Service Computing Systems in Digital Twins
  openalex 2023 置信度 0.90 Network Security and Intrusion DetectionSoftware-Defined Networks and 5GSmart Grid Security and Resilience
• A review of critical challenges in MI-BCI: From conventional to deep learning methods
  openalex 2022 置信度 0.90 EEG and Brain-Computer InterfacesAdvanced Memory and Neural ComputingNeuroscience and Neural Engineering
• HYDRA: A Hybrid Resistance Drift Resilient Architecture for Phase Change Memory-Based Neural Network Accelerators
  openalex 2024 置信度 0.90 Advanced Memory and Neural ComputingPhase-change materials and chalcogenidesParallel Computing and Optimization Techniques
• URBAN-i: From urban scenes to mapping slums, transport modes, and pedestrians in cities using deep learning and computer vision
  openalex 2019 置信度 0.90 Human Mobility and Location-Based AnalysisAdvanced Neural Network ApplicationsSmart Cities and Technologies
• Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs
  openalex 2016 置信度 0.90 Retinal Imaging and AnalysisRetinal Diseases and TreatmentsRetinal and Optic Conditions
• Intra-subject class-incremental deep learning approach for EEG-based imagined speech recognition
  openalex 2022 置信度 0.90 EEG and Brain-Computer InterfacesBlind Source Separation TechniquesAdvanced Memory and Neural Computing
• An Adaptive Image Watermarking Algorithm Based on Neural Network
  openalex 2011 置信度 0.90 Advanced Steganography and Watermarking TechniquesDigital Media Forensic DetectionChaos-based Image/Signal Encryption
• A model-driven approach to machine learning and software modeling for the IoT
  openalex 2022 置信度 0.90 Software System Performance and ReliabilityScientific Computing and Data ManagementAdvanced Software Engineering Methodologies
• E-prop on SpiNNaker 2: Exploring online learning in spiking RNNs on neuromorphic hardware
  openalex 2022 置信度 0.90 Advanced Memory and Neural ComputingFerroelectric and Negative Capacitance DevicesNeural Networks and Reservoir Computing
• A QoS-Aware Technique for Computation Offloading in IoT-Edge Platforms Using a Convolutional Neural Network and Markov Decision Process
  openalex 2023 置信度 0.90 Advanced Technologies in Various FieldsIoT and Edge/Fog ComputingAir Quality Monitoring and Forecasting
• Multimodal data analysis of epileptic EEG and rs-fMRI via deep learning and edge computing
  openalex 2020 置信度 0.90 EEG and Brain-Computer InterfacesFunctional Brain Connectivity StudiesBig Data and Digital Economy
• Information processing via physical soft body
  openalex 2015 置信度 0.90 Neural Networks and Reservoir ComputingNeural dynamics and brain functionAdvanced Memory and Neural Computing
• A million spiking-neuron integrated circuit with a scalable communication network and interface
  openalex 2014 置信度 0.90 Advanced Memory and Neural ComputingNeural dynamics and brain functionNeuroscience and Neural Engineering
• Efficient Processing of Deep Neural Networks: A Tutorial and Survey
  openalex 2017 置信度 0.90 Advanced Neural Network ApplicationsAdvanced Memory and Neural ComputingFerroelectric and Negative Capacitance Devices
• Introduction to spiking neural networks: Information processing, learning and applications
  openalex 2011 置信度 0.90 Advanced Memory and Neural ComputingNeural dynamics and brain functionNeural Networks and Reservoir Computing
• Information Processing Capacity of Dynamical Systems
  openalex 2012 置信度 0.90 Neural Networks and Reservoir ComputingNeural Networks and ApplicationsNeural dynamics and brain function
• A transfer learning-based CNN and LSTM hybrid deep learning model to classify motor imagery EEG signals
  openalex 2022 置信度 0.90 EEG and Brain-Computer InterfacesNeuroscience and Neural EngineeringAdvanced Memory and Neural Computing
• Fading memory and kernel properties of generic cortical microcircuit models
  openalex 2004 置信度 0.90 Advanced Memory and Neural ComputingNeural Networks and Reservoir ComputingNeural dynamics and brain function
• Evolving spiking neural networks for personalised modelling, classification and prediction of spatio-temporal patterns with a case study on stroke
  openalex 2014 置信度 0.90 Advanced Memory and Neural ComputingNeural Networks and Reservoir ComputingNeural Networks and Applications
• Spike-FlowNet: Event-Based Optical Flow Estimation with Energy-Efficient Hybrid Neural Networks
  openalex 2020 置信度 0.90 Advanced Memory and Neural ComputingNeural Networks and Reservoir ComputingNeural dynamics and brain function
• Spiking Neural Network Integrated Circuits: A Review of Trends and Future Directions
  openalex 2022 置信度 0.90 Advanced Memory and Neural ComputingNeural Networks Stability and SynchronizationFerroelectric and Negative Capacitance Devices
• SuperSpike: Supervised Learning in Multilayer Spiking Neural Networks
  openalex 2018 置信度 0.90 Advanced Memory and Neural ComputingNeural dynamics and brain functionNeural Networks and Reservoir Computing
• Cross-layer transmission realized by light-emitting memristor for constructing ultra-deep neural network with transfer learning ability
  openalex 2024 置信度 0.90 Advanced Memory and Neural ComputingNeural Networks and Reservoir ComputingCCD and CMOS Imaging Sensors
• Automated Classification of L/R Hand Movement EEG Signals using Advanced Feature Extraction and Machine Learning
  openalex 2013 置信度 0.90 EEG and Brain-Computer InterfacesNeuroscience and Neural EngineeringAdvanced Memory and Neural Computing
• Physical Implementation of Reservoir Computing through Electrochemical Reaction
  openalex 2021 置信度 0.90 Neural Networks and Reservoir ComputingAdvanced Memory and Neural ComputingNeural dynamics and brain function
• Neural Trojans
  openalex 2017 置信度 0.90 Adversarial Robustness in Machine LearningPhysical Unclonable Functions (PUFs) and Hardware SecurityAdvanced Memory and Neural Computing
• Dynamic Adaptive Neural Network Array
  openalex 2014 置信度 0.90 Advanced Memory and Neural ComputingNeural Networks and ApplicationsFerroelectric and Negative Capacitance Devices
• Zip-NeRF: Anti-Aliased Grid-Based Neural Radiance Fields
  openalex 2023 置信度 0.90 3D Shape Modeling and AnalysisComputer Graphics and Visualization TechniquesAdvanced Neural Network Applications
• Optical synaptic devices with ultra-low power consumption for neuromorphic computing
  openalex 2022 置信度 0.90 Advanced Memory and Neural ComputingNeural Networks and Reservoir Computing2D Materials and Applications
• Suppression of ferroresonance using passive memristor emulator
  openalex 2021 置信度 0.90 Advanced Memory and Neural ComputingNeural Networks and Reservoir ComputingNeuroscience and Neural Engineering
• Generative machine learning algorithm for lattice structures with superior mechanical properties
  openalex 2022 置信度 0.90 Cellular and Composite StructuresAdditive Manufacturing and 3D Printing TechnologiesInnovations in Concrete and Construction Materials
• Development of a high-performance general purpose neuro-computer composed of 512 digital neurons
  openalex 2005 置信度 0.90 Neural Networks and ApplicationsAdvanced Memory and Neural ComputingCCD and CMOS Imaging Sensors
• Reservoir computing using dynamic memristors for temporal information processing
  openalex 2017 置信度 0.90 Advanced Memory and Neural ComputingNeural Networks and Reservoir ComputingNeural dynamics and brain function
• Fast and energy-efficient neuromorphic deep learning with first-spike times
  openalex 2019 置信度 0.90 Advanced Memory and Neural ComputingNeural dynamics and brain functionFerroelectric and Negative Capacitance Devices
• Multifunctional Two-Terminal Optoelectronic Synapse Based on an Organic Semiconductor Film
  openalex 2023 置信度 0.90 Advanced Memory and Neural ComputingNeural Networks and Reservoir ComputingPhotoreceptor and optogenetics research
• Topological Insulator Optoelectronic Synapses for High‐Accuracy Binary Image Recognition using Recurrent Neural Networks
  openalex 2022 置信度 0.90 Advanced Memory and Neural ComputingPhotoreceptor and optogenetics researchNeural Networks and Reservoir Computing
• Nanoscale neuromorphic networks and criticality: a perspective
  openalex 2021 置信度 0.90 Advanced Memory and Neural ComputingNeural dynamics and brain functionNeural Networks and Reservoir Computing
• Point-Based Neural Scene Rendering for Street Views
  openalex 2023 置信度 0.90 Advanced Vision and ImagingComputer Graphics and Visualization TechniquesRemote Sensing and LiDAR Applications
• Hardware Realization of the Pattern Recognition with an Artificial Neuromorphic Device Exhibiting a Short-Term Memory
  openalex 2019 置信度 0.90 Advanced Memory and Neural ComputingNeural Networks and Reservoir ComputingCCD and CMOS Imaging Sensors
• A molecular neuromorphic network device consisting of single-walled carbon nanotubes complexed with polyoxometalate
  openalex 2018 置信度 0.90 Advanced Memory and Neural ComputingNeural Networks and Reservoir ComputingNeural dynamics and brain function
• Differential diagnosis of neurodegenerative dementias with the explainable MRI based machine learning algorithm MUQUBIA
  openalex 2023 置信度 0.90 Dementia and Cognitive Impairment ResearchAdvanced Neuroimaging Techniques and ApplicationsNeurological Disease Mechanisms and Treatments
• Neuro-inspired computing chips
  openalex 2020 置信度 0.90 Advanced Memory and Neural ComputingFerroelectric and Negative Capacitance DevicesNeuroscience and Neural Engineering
• Solar-stimulated optoelectronic synapse based on organic heterojunction with linearly potentiated synaptic weight for neuromorphic computing
  openalex 2019 置信度 0.90 Advanced Memory and Neural ComputingPhotoreceptor and optogenetics researchNeural dynamics and brain function
• Explainable predictive business process monitoring using gated graph neural networks
  openalex 2020 置信度 0.90 Business Process Modeling and AnalysisSoftware System Performance and ReliabilityBlockchain Technology Applications and Security
• TiO2/Bi4Ti3O12 heterojunction optoelectronic synaptic devices for simulating associative memory and neuromorphic computation
  openalex 2025 置信度 0.90 Advanced Memory and Neural ComputingNeural Networks and Reservoir ComputingNeuroscience and Neural Engineering
• Sparse Binary Matrix-Vector Multiplication on Neuromorphic Computers
  openalex 2021 置信度 0.90 Advanced Memory and Neural ComputingFerroelectric and Negative Capacitance DevicesNeural Networks and Reservoir Computing
• Autonomous UAV navigation using deep learning-based computer vision frameworks: A systematic literature review
  openalex 2024 置信度 0.90 Robotics and Sensor-Based LocalizationRobotic Path Planning AlgorithmsAdvanced Neural Network Applications
• Rethinking the Inception Architecture for Computer Vision
  openalex 2016 置信度 0.90 Advanced Neural Network ApplicationsAdversarial Robustness in Machine LearningAnomaly Detection Techniques and Applications
• Transferring a deep learning model from healthy subjects to stroke patients in a motor imagery brain–computer interface
  openalex 2023 置信度 0.90 EEG and Brain-Computer InterfacesGaze Tracking and Assistive TechnologyFunctional Brain Connectivity Studies
• Superlow Power Consumption Memristor Based on Borphyrin–Deoxyribonucleic Acid Composite Films as Artificial Synapse for Neuromorphic Computing
  openalex 2023 置信度 0.90 Advanced Memory and Neural ComputingPhotoreceptor and optogenetics researchNeuroscience and Neural Engineering
• Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communication
  openalex 2004 置信度 0.90 Neural Networks and Reservoir ComputingAdvanced Memory and Neural ComputingNeural Networks and Applications
• A Secure and Privacy-Preserving Machine Learning Model Sharing Scheme for Edge-Enabled IoT
  openalex 2021 置信度 0.90 Cryptography and Data SecurityPrivacy-Preserving Technologies in DataBlockchain Technology Applications and Security
• Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields
  openalex 2021 置信度 0.90 Computer Graphics and Visualization TechniquesAdvanced Vision and ImagingMedical Image Segmentation Techniques
• PZT-Enabled MoS2 Floating Gate Transistors: Overcoming Boltzmann Tyranny and Achieving Ultralow Energy Consumption for High-Accuracy Neuromorphic Computing
  openalex 2023 置信度 0.90 Advanced Memory and Neural ComputingFerroelectric and Negative Capacitance DevicesNeural Networks and Reservoir Computing
• Artificial Astrocyte Memristor with Recoverable Linearity for Neuromorphic Computing
  openalex 2021 置信度 0.90 Advanced Memory and Neural ComputingNeuroscience and Neural EngineeringFerroelectric and Negative Capacitance Devices
• POD: PCM-Based Computing Platform for Object Detection in Biomedical Imaging Application
  openalex 2024 置信度 0.90 Advanced Memory and Neural ComputingFerroelectric and Negative Capacitance DevicesAdvanced Neural Network Applications
• CsPbBr3/graphene nanowall artificial optoelectronic synapses for controllable perceptual learning
  openalex 2023 置信度 0.90 Advanced Memory and Neural ComputingPhotoreceptor and optogenetics researchNeural Networks and Reservoir Computing
• A low-power, high-accuracy with fully on-chip ternary weight hardware architecture for Deep Spiking Neural Networks
  openalex 2022 置信度 0.90 Advanced Memory and Neural ComputingFerroelectric and Negative Capacitance DevicesNeural dynamics and brain function
• Application of Neural Network Sample Training Algorithm in Economic Information Management System
  openalex 2022 置信度 0.90 Advanced Technologies in Various FieldsAI and HR Technologies
• Neural radiance fields for multi-scale constraint-free 3D reconstruction and rendering in orchard scenes
  openalex 2024 置信度 0.90 Advanced Vision and ImagingComputer Graphics and Visualization TechniquesRemote Sensing and LiDAR Applications
• Motor imagery EEG signal classification using novel deep learning algorithm
  openalex 2025 置信度 0.90 EEG and Brain-Computer InterfacesNon-Invasive Vital Sign MonitoringMuscle activation and electromyography studies
• The coexistence of threshold and memory switching characteristics of ALD HfO 2 memristor synaptic arrays for energy-efficient neuromorphic computing
  openalex 2020 置信度 0.90 Advanced Memory and Neural ComputingNeuroscience and Neural EngineeringFerroelectric and Negative Capacitance Devices
• Distributed Routing Strategy Based on Machine Learning for LEO Satellite Network
  openalex 2018 置信度 0.90 Satellite Communication SystemsWireless Communication Networks ResearchSoftware-Defined Networks and 5G
• Comparative Assessment of Neural Radiance Fields and Photogrammetry in Digital Heritage: Impact of Varying Image Conditions on 3D Reconstruction
  openalex 2024 置信度 0.90 3D Surveying and Cultural HeritageAdvanced Vision and ImagingComputer Graphics and Visualization Techniques
• Tiny-MLOps: a framework for orchestrating ML applications at the far edge of IoT systems
  openalex 2022 置信度 0.90 Anomaly Detection Techniques and ApplicationsIoT and Edge/Fog ComputingContext-Aware Activity Recognition Systems
• Comprehensive SNN Compression Using ADMM Optimization and Activity Regularization
  openalex 2021 置信度 0.90 Advanced Memory and Neural ComputingFerroelectric and Negative Capacitance DevicesNeural Networks and Reservoir Computing
• Phase-Adaptive Federated Learning for Privacy-Preserving Personalized Travel Itinerary Generation
  We propose Phase-Adaptive Federated Learning (PAFL), a novel framework for privacy-preserving personalized travel itinerary generation that dynamically balances privacy and utility through a phase-dependent aggregation mechanism inspired by phase-change materi…
  openalex Xiaolong Chen, Hongfeng Zhang, Cora Un In Wong 2025-06-02 置信度 0.84 Computer sciencePhase (matter)Internet privacyChemistryOrganic chemistry
• DRACO: Decentralized Asynchronous Federated Learning Over Row-Stochastic Wireless Networks
  Emerging technologies and use cases, such as smart Internet of Things (IoT), Internet of Agents, and Edge AI, have generated significant interest in training neural networks over fully decentralized, serverless networks. A major obstacle in this context is ens…
  openalex Eunjeong Jeong, Marios Kountouris 2025-01-01 置信度 0.84 Asynchronous communicationComputer scienceWirelessDistributed computingWireless network
• ADVANCEMENTS IN FEDERATED LEARNING FOR SECURE DATA SHARING IN FINANCIAL SERVICES
  This paper explores the application of Federated Learning (FL) in the financial sector, focusing on enhancing security and privacy in key areas such as fraud detection, Anti-Money Laundering (AML) compliance, and biometric authentication systems. FL enables co…
  openalex Nkem Belinda Unuigbokhai, Godfrey Oise, Babalola Eyitemi Akilo, Onyemaechi Clement Nwabuokei 等 2025-05-31 置信度 0.84 Data sharingBusinessFinanceComputer scienceFinancial services
• pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning
  Federated learning (FL) is an emerging machine learning paradigm in which a central server coordinates multiple participants (clients) collaboratively to train on decentralized data. In practice, FL often faces statistical, system, and model heterogeneities, w…
  openalex Liping Yi, Han Yu, Gang Wang, Xiaoguang Liu 等 2023-10-20 置信度 0.82 Computer scienceFederated learningComputer architectureArtificial intelligence
• Enhancing agricultural commodity price forecasting with deep learning
  Accurate forecasting of agricultural commodity prices is essential for market planning and policy formulation, especially in agriculture-dependent economies like India. Price volatility, driven by factors such as weather variability and market demand fluctuati…
  openalex R. L. Manogna, Vijay Dharmaji, S Sarang 2025-07-01 置信度 0.84 Autoregressive integrated moving averageDeep learningArtificial intelligenceMean absolute percentage errorMean squared error
• FedMEM: Adaptive Personalized Federated Learning Framework for Heterogeneous Mobile Edge Environments
  With the growth of the Internet of Things (IoT) and communication technologies, edge devices have become more diverse. This diversity has increased the computational load on these systems and led to differences between devices. In mobile edge computing, variat…
  openalex Chen Ximing, He Xilong, Cheng Du, WU Tie-jun 等 2025-04-14 置信度 0.84 Computer scienceEnhanced Data Rates for GSM EvolutionPersonalized learningHuman–computer interactionAdaptive learning
• Scale-MIA: A Scalable Model Inversion Attack against Secure Federated Learning via Latent Space Reconstruction
  Federated learning is known for its capability to safeguard the participants' data privacy.However, recently emerged model inversion attacks (MIAs) have shown that a malicious parameter server can reconstruct individual users' local data samples from model upd…
  openalex Shanghao Shi, Ning Wang, Xiao Yang, Chaoyu Zhang 等 2025-01-01 置信度 0.84 ScalabilityComputer scienceInversion (geology)Scale (ratio)Space (punctuation)
• Quantum-Driven Reinforcement Learning for Spectral Energy Optimization in Massive MIMO Hybrid Beamforming for 6G
  Abstract The evolution of 6G wireless networks demands highly efficient beamforming strategies to optimize spectral and energy efficiency in massive MIMO systems. This study introduces a Quantum-Driven Reinforcement Learning (QDRL) framework for Spectral Energ…
  openalex R. Krishnamoorthy, M. Amina Begum, Lakshmana Phaneendra Maguluri, Maha Abdelhaq 等 2025-10-01 置信度 0.84 Computer scienceReinforcement learningMIMOBeamformingEnergy consumption
• Emerging role of generative AI in renewable energy forecasting and system optimization
  • Generative AI improves RES forecasting accuracy by up to 25 %. • GANs and VAEs optimize microgrid and storage operations. • Federated learning enables privacy-preserving energy model training. • Black-box models pose interpretability and regulatory challenge…
  openalex Erdiwansyah Erdiwansyah, Rizalman Mamat, Syafrizal Syafrizal, Mohd Fairusham Ghazali 等 2025-07-15 置信度 0.84 Renewable energyGenerative grammarComputer scienceArtificial intelligenceEngineering
• Advancements in Small-Object Detection (2023–2025): Approaches, Datasets, Benchmarks, Applications, and Practical Guidance
  Small-object detection (SOD) remains an important and growing challenge in computer vision and is the backbone of many applications, including autonomous vehicles, aerial surveillance, medical imaging, and industrial quality control. Small objects, in pixels, …
  openalex Ali Aldubaikhi, Sarosh Patel 2025-11-07 置信度 0.80 Computer scienceRobustness (evolution)Software deploymentData scienceArtificial intelligence
• UAV-Assisted Federated Learning With Robust Resource and Trajectory Optimization Under Location Uncertainties
  Federated learning (FL) has emerged as a promising solution to facilitate the deployment of artificial intelligence (AI) on wireless devices. However, heterogeneity of wireless devices, including disparities in computation capabilities, data sizes, and energy …
  openalex Chen Wang, Xiao Tang, Zehui Xiong, Daosen Zhai 等 2025-09-26 置信度 0.84 Computer scienceCoordinate descentTrajectoryComputationWireless
• Machine learning and deep learning in medicine and neuroimaging
  Artificial intelligence is the science and engineering of machines that can mimic human intelligence. Machine learning is the subfield of artificial intelligence in which computers have the ability to learn and iteratively improve their performance without bei…
  openalex Iván Sánchez Fernández, Jurriaan M. Peters 2023-02-07 置信度 0.82 Artificial intelligenceDeep learningComputer scienceMachine learningConvolutional neural network
• Secure blockchain integrated deep learning framework for federated risk-adaptive and privacy-preserving IoT edge intelligence sets
  An enormous demand for a secure, scalable, intelligent edge computing framework has emerged for the exponentially increasing number of Internet of Things (IoT) devices for any substrate of modern digital infrastructure. These edge nodes distributed across hete…
  openalex K. Swathi, Putta Durga, K. Venkata Prasad, A Krishna Chaitanya 等 2025-11-20 置信度 0.84 Computer scienceEdge computingDeep learningBlockchainEdge device
• Federated Transfer Learning for Tomato Leaf Disease Detection Using Neuro-Graph Hybrid Model
  Plant diseases are currently a major threat to agricultural economies and food availability, having a negative environmental impact. Despite being a promising line of research, current approaches struggle with poor cross-site generalization, limited labels and…
  openalex Aurora-Felicia Cristea, Ciprian Dobre 2025-12-15 置信度 0.84 Robustness (evolution)Computer scienceMachine learningTransfer of learningArtificial intelligence
• Blockchain-based personalized federated learning framework for drug recommendation systems resilient to model poisoning
  Abstract Federated learning enables multiple healthcare entities to collaboratively train a global model while ensuring patient data privacy through local model training without sharing raw data. However, FL remains vulnerable to adversarial attacks such as mo…
  openalex Sina Apak, İsmail Tuncer Değim, Samaneh Zahertar 2026-01-01 置信度 0.84 Computer scienceFederated learningRobustness (evolution)Software deploymentRecommender system
• Automated machine learning with interpretation: A systematic review of methodologies and applications in healthcare
  Abstract Machine learning (ML) has achieved substantial success in performing healthcare tasks in which the configuration of every part of the ML pipeline relies heavily on technical knowledge. To help professionals with borderline expertise to better use ML t…
  openalex Han Yuan, Kunyu Yu, Feng Xie, M. Liu 等 2024-08-27 置信度 0.84 Health careArtificial intelligenceComputer scienceInterpretation (philosophy)Data science
• Federated Learning‐Based Intrusion Detection Systems for Massive IoT
  Despite the significant benefits that the 6G-enabled massive Internet of Things (IoT) applications will bring to the economy and society in the coming years, it is expected that the exponential increase in the number and the diversity of IoT devices and connec…
  openalex Filippos Pelekoudas‐Oikonomou, Parya Haji Mirzaee, Waleed Hathal, Γεώργιος Μαντάς 等 2024-12-13 置信度 0.84 Intrusion detection systemComputer scienceInternet of ThingsData miningComputer security
• Robust Federated Learning Against Data Poisoning Attacks: Prevention and Detection of Attacked Nodes
  Federated learning (FL) enables collaborative model building among a large number of participants without sharing sensitive data to the central server. Because of its distributed nature, FL has limited control over local data and the corresponding training pro…
  openalex Pretom Roy Ovi, Aryya Gangopadhyay 2025-07-25 置信度 0.84 Computer scienceRobustness (evolution)Training setFederated learningMachine learning
• The Sugeno Integral Used for Federated Learning with Uncertainty for Unbalanced Data
  Data is crucial in the digital economy. Many businesses collect and use their data to enhance their performance. However, limited data or low data quality can hinder model development, particularly in dynamic environments. To overcome this, companies collectin…
  openalex Anna Wilbik, Barbara Pȩkala, Jarosław Szkoła, Krzysztof Dyczkowski 2023-08-13 置信度 0.82 Federated learningComputer scienceMechanism (biology)Data sharingQuality (philosophy)
• Privacy-Preserving Diabetes and Heart Disease Prediction via Federated Learning and WCO
  Diabetes, afflicting 537 million worldwide, is a prevalent and lethal non-communicable ailment. Its onset, influenced by factors like obesity and family history, manifests symptoms such as frequent urination. Long-term complications encompass heart, kidney, an…
  openalex Sachikanta Dash, Sasmita Padhy, Preetam Suman, Sandip Mal 等 2025-08-23 置信度 0.84 Computer scienceDiabetes mellitusArtificial intelligenceMachine learningMedicine
• Federated Learning for Wireless Communications
  In the past few years, machine learning (ML) techniques have been introduced for the physical layer applications in wireless communications. In contrast to employing centralized learning (CL) techniques, federated learning (FL) presents lower communication ove…
  openalex Ahmet M. Elbir, Wei Shi 2024-12-13 置信度 0.84 WirelessComputer scienceTelecommunicationsComputer network
• Certifying the Right to Be Forgotten: Primal–Dual Optimization for Sample and Label Unlearning in Vertical Federated Learning
  Federated unlearning has become an attractive approach to address privacy concerns in collaborative machine learning, for situations when sensitive data are remembered by AI models during the machine learning process. It enables the removal of specific data in…
  openalex Yu Jiang, Xindi Tong, Ziyao Liu, Xiaoxi Zhang 等 2025-01-01 置信度 0.84 Computer scienceOverhead (engineering)Federated learningSample (material)Feature (linguistics)
• DFCA: Decentralized Federated Clustering Algorithm
  Clustered Federated Learning has emerged as an effective approach for handling heterogeneous data across clients by partitioning them into clusters with similar or identical data distributions. However, most existing methods, including the Iterative Federated …
  openalex Jonas Kirch, S. Becker, Tiago Koketsu Rodrigues, Stefan Harmeling 2026-03-02 置信度 0.84 Computer scienceCluster analysisBottleneckFederated learningRobustness (evolution)
• Novel Federated Graph Contrastive Learning for IoMT Security: Protecting Data Poisoning and Inference Attacks
  Malware evolution presents growing security threats for resource-constrained Internet of Medical Things (IoMT) devices. Conventional federated learning (FL) often suffers from slow convergence, high communication overhead, and fairness issues in dynamic IoMT e…
  openalex Amarudin Daulay, Kalamullah Ramli, Ruki Harwahyu, Taufik Hidayat 等 2025-07-31 置信度 0.84 Computer scienceInferenceComputer securityGraphTheoretical computer science
• Trusted Data Sharing Mechanism Based on Blockchain and Federated Learning in Space‐Air‐Ground Integrated Networks
  Network data is distributed data on electricity, with the explosive growth of network data, and it has become an inevitable trend of network development to synergized and shared crossdomain scattered data and enhances the value transmission of network data. Fe…
  openalex Da Li, Qinglei Guo, Chao Yang, Han Yan 2022-01-01 置信度 0.82 Computer scienceData sharingComputer securityTrusted third partyIncentive
• Deep Learning Approaches for EEG-Motor Imagery-Based BCIs: Current Models, Generalization Challenges, and Emerging Trends
  This study critically examines the evolution of deep learning (DL) for electroencephalogram (EEG) based motor imagery (MI) decoding with a focus on real-time Brain Computer Interfaces (BCIs) development. Prior studies often prioritize accuracy in isolation, ne…
  openalex Aaqib Raza, Mohd Zuki Yusoff 2025-01-01 置信度 0.84 Motor imageryBrain–computer interfaceElectroencephalographyComputer scienceGeneralization
• The blockchain‐based privacy‐preserving searchable attribute‐based encryption scheme for federated learning model in IoMT
  Abstract Federated learning enables training healthcare diagnostic models across multiple decentralized devices containing local private health data samples, without transferring data to a central server, providing privacy‐preserving services for healthcare pr…
  openalex Ziyu Zhou, Na Wang, Jianwei Liu, Junsong Fu 等 2024-08-20 置信度 0.84 Computer scienceBlockchainScheme (mathematics)EncryptionLearning with errors
• FedNolowe: A normalized loss-based weighted aggregation strategy for robust federated learning in heterogeneous environments
  Federated Learning supports collaborative model training across distributed clients while keeping sensitive data decentralized. Still, non-independent and identically distributed data pose challenges like unstable convergence and client drift. We propose Feder…
  openalex Duy-Dong Le, Nguyen Huynh Tuong, Anh-Khoa Tran, Minh-Son Dao 等 2025-08-14 置信度 0.84 Computer scienceFederated learningData aggregatorArtificial intelligenceComputer network
• Blockchain-Enabled Hierarchical Federated Learning Framework for Anomaly Detection in IoT Systems
  The rapid expansion of the Internet of Things (IoT) across domains such as industrial automation, smart healthcare, and intelligent transportation has intensified security challenges, particularly in terms of detecting anomalies across large-scale, heterogeneo…
  openalex Haya Alharthi, Suhair Alshehri, Manal Kalkatawi 2025-12-11 置信度 0.84 Federated learningComputer scienceInternet of ThingsAnomaly detectionTrustworthiness
• FedCache: A Knowledge Cache-driven Federated Learning Architecture for Personalized Edge Intelligence
  Edge Intelligence (EI) enables Artificial Intelligence (AI) applications to run at the edge, where data analysis and decision-making can be performed in real-time and close to data sources. To protect data privacy and unify data silos distributed among end dev…
  openalex Zhiyuan Wu, Sheng Sun, Yuwei Wang, Min Liu 等 2023-06-13 置信度 0.82 Computer scienceCacheOverhead (engineering)Enhanced Data Rates for GSM EvolutionArchitecture
• Towards fair decentralized benchmarking of healthcare AI algorithms with the Federated Tumor Segmentation (FeTS) challenge
  Computational competitions are the standard for benchmarking medical image analysis algorithms, but they typically use small curated test datasets acquired at a few centers, leaving a gap to the reality of diverse multicentric patient data. To this end, the Fe…
  openalex Maximilian Zenk, Ujjwal Baid, Sarthak Pati, Akis Linardos 等 2025-07-07 置信度 0.84 BenchmarkingBenchmark (surveying)Computer scienceSegmentationArtificial intelligence
• Network-based intrusion detection using deep learning technique
  A high growth rate in network traffic and the complexity of cyber threats have made it necessary to create more effective and flexible intrusion detection systems. Most traditional Network-based Intrusion Detection Systems (NIDS) can become weak at detecting n…
  openalex Muhammad Farhan, Hafiz Waheed ud din, S. M. Wazid Ullah, Muhammad Sajjad Hussain 等 2025-07-15 置信度 0.84 Computer scienceIntrusion detection systemArtificial intelligenceDeep learningIntrusion
• Enhanced Privacy and Communication Efficiency in Non-IID Federated Learning With Adaptive Quantization and Differential Privacy
  Federated learning (FL) is a distributed machine learning method where multiple devices collaboratively train a model under the management of a central server without sharing underlying data. One of the key challenges of FL is the communication bottleneck caus…
  openalex Emre Ardıç, Yakup Genç 2025-01-01 置信度 0.84 Differential privacyComputer scienceInformation privacyQuantization (signal processing)Privacy software
• Recent Methodological Advances in Federated Learning for Healthcare
  openalex Fan Zhang, Daniel Kreuter, Yi‐Chen Chen, Sören Dittmer 等 2023-10-04 置信度 0.71 Computer scienceFederated learningPoolingHealth careCompromise
• Advancing Fusion with Machine Learning Research Needs Workshop Report
  Abstract Machine learning and artificial intelligence (ML/AI) methods have been used successfully in recent years to solve problems in many areas, including image recognition, unsupervised and supervised classification, game-playing, system identification and …
  openalex D.A. Humphreys, Ana Kupresanin, Mark D. Boyer, J.M. Canik 等 2020-08-01 置信度 0.82 Artificial intelligenceComputer scienceMachine learningIdentification (biology)Robotics
• A Survey on Collaborative Learning for Intelligent Autonomous Systems
  This survey examines approaches to promote Collaborative Learning in distributed systems for emergent Intelligent Autonomous Systems (IAS). The study involves a literature review of Intelligent Autonomous Systems based on Collaborative Learning, analyzing aspe…
  openalex Julio César Santos dos Anjos, Kassiano J. Matteussi, Fernanda C. Orlandi, Jorge Luís Victória Barbosa 等 2023-09-28 置信度 0.82 Computer scienceSoftware deploymentBig dataKnowledge managementCollaborative learning
• LLM-Based Agents for Tool Learning: A Survey
  Abstract Human beings capable of making and using tools can accomplish tasks far beyond their innate abilities, and this paradigm of integration with tools may not be limited to humans themselves. Recently, the large language model (LLM) has demonstrated immen…
  openalex Weikai Xu, Chengrui Huang, Shen Gao, Shuo Shang 2025-06-26 置信度 0.82 Computer scienceData science
• Identifying significant features in adversarial attack detection framework using federated learning empowered medical IoT network security
  The expansion of the Internet of Medical Things (IoHT) presents significant advantages for healthcare over improved data-driven insights and connectivity and offers critical cybersecurity challenges. Attacks are a serious risk for neural network security; rece…
  openalex Sanaa Sharaf, Sameer Nooh 2025-08-26 置信度 0.84 Adversarial systemComputer scienceInternet of ThingsComputer securityNetwork security
• Advances in Neuroimaging and Deep Learning for Emotion Detection: A Systematic Review of Cognitive Neuroscience and Algorithmic Innovations
  Background/Objectives: The following systematic review integrates neuroimaging techniques with deep learning approaches concerning emotion detection. It, therefore, aims to merge cognitive neuroscience insights with advanced algorithmic methods in pursuit of a…
  openalex Constantinos Halkiopoulos, Evgenia Gkintoni, Anthimos Aroutzidis, Hera Antonopoulou 2025-02-13 置信度 0.84 NeuroimagingCognitionModalitiesComputer scienceDeep learning
• Adversarial machine learning: a review of methods, tools, and critical industry sectors
  Abstract The rapid advancement of Artificial Intelligence (AI), particularly Machine Learning (ML) and Deep Learning (DL), has produced high-performance models widely used in various applications, ranging from image recognition and chatbots to autonomous drivi…
  openalex Sotiris Pelekis, Thanos Koutroubas, Afroditi Blika, Anastasis Berdelis 等 2025-05-02 置信度 0.84 Computer scienceAdversarial systemArtificial intelligenceMachine learningEngineering management
• Enhancing Efficiency in Multidevice Federated Learning through Data Selection
  Ubiquitous wearable and mobile devices provide access to a diverse set of data. However, the mobility demand for our devices naturally imposes constraints on their computational and communication capabilities. A solution is to locally learn knowledge from data…
  openalex Fan Mo, Mohammad Malekzadeh, Soumyajit Chatterjee, Fahim Kawsar 等 2022-11-08 置信度 0.82 Computer scienceBenchmark (surveying)Partition (number theory)Federated learningProcess (computing)
• Digital Twin: Enabling Technologies, Challenges and Open Research
  Digital Twin technology is an emerging concept that has become the centre of attention for industry and, in more recent years, academia. The advancements in industry 4.0 concepts have facilitated its growth, particularly in the manufacturing industry. The Digi…
  openalex Aidan Fuller, Zhong Fan, Charles Day, Chris Barlow 2020-01-01 置信度 0.78 Computer scienceOpen researchWorld Wide Web
• An Asynchronous Federated Learning Aggregation Method Based on Adaptive Differential Privacy
  Federated learning is a distributed machine learning technique that allows multiple devices to collaborate on learning a shared model without exchanging data. It can be used to improve model accuracy while protecting user privacy. However, traditional federate…
  openalex Jiawen Wu, Geming Xia, Hongwei Huang, Chaodong Yu 等 2025-07-16 置信度 0.84 Differential privacyAsynchronous communicationComputer scienceFederated learningAsynchronous learning
• Federated learning for automotive applications
  This paper presents and evaluates a new distributed learning technology, called federated learning, and its applications in automotive systems. We review and classify existing approaches to federated learning, focusing on its implementation in connected vehicl…
  openalex William Lindskog-Münzing, Christian Prehofer 2025-05-23 置信度 0.84 Automotive industryComputer scienceBusinessManufacturing engineeringEngineering
• Collaboration of IoT devices in smart home scenarios: algorithm research based on graph neural networks and federated learning
  Traditional IoT device collaboration is usually static and cannot adjust the collaboration mode between devices according to various changes, which limits work efficiency. To this end, an IoT device collaboration optimization algorithm based on graph neural ne…
  openalex Yuanquan Zhong 2025-01-09 置信度 0.84 Computer scienceInternet of ThingsArtificial neural networkGraphArtificial intelligence
• DRL-Based Joint Aggregation Frequency and Edge Association for Energy-Efficient Hierarchical Federated Learning
  Hierarchical Federated Learning (HFL) has been proposed to achieve large-scale model training and more efficient communication, surpassing conventional Federated Learning (FL). However, inappropriate aggregation frequency and edge association in HFL result in …
  openalex Yijing Ren, Changxiang Wu, Daniel K. C. So, Jie Tang 2025-04-09 置信度 0.84 Computer scienceJoint (building)Association (psychology)Enhanced Data Rates for GSM EvolutionArtificial intelligence
• Asynchronous Byzantine Federated Learning
  Federated learning (FL) enables a set of geographically distributed clients to collectively train a model through a server. Classically, the training process is synchronous, but can be made asynchronous to maintain its speed in presence of slow clients and in …
  openalex Bart Cox, Abele Mălan, Lydia Y. Chen, Jérémie Decouchant 2024-06-03 置信度 0.84 Byzantine architectureAsynchronous communicationComputer scienceByzantine fault toleranceAsynchronous learning
• SECURE PREDICTIVE MAINTENANCE FOR INDUSTRIAL SYSTEMS USING FEDERATED LEARNING
  In this paper, a secure and scalable predictive maintenance approach for Industry 4.0 using Federated Learning (FL) and Artifficial Intelligence (AI) is addressed.Unlike other approaches, FL maintains data on the premises, which guarantees privacy and regulato…
  openalex 2025-01-01 置信度 0.84 Predictive maintenanceComputer scienceReliability engineeringEngineering
• When Fine-Tuning LLMs Meets Data Privacy: An Empirical Study of Federated Learning in LLM-Based Program Repair
  Software systems have been evolving rapidly and inevitably introducing bugs at an increasing rate, leading to significant maintenance costs. While large language models (LLMs) have demonstrated remarkable potential in enhancing software development and mainten…
  openalex Wenqiang Luo, Jacky Keung, Boyang Yang, He Ye 等 2025-05-01 置信度 0.84 Computer scienceEmpirical researchInternet privacyComputer securityPhilosophy
• FLUID: Dynamic Model-Agnostic Federated Learning with Pruning and Knowledge Distillation for Maritime Predictive Maintenance
  Predictive maintenance (PdM) is vital to maritime operations; however, the traditional deep learning solutions currently offered heavily depend on centralized data aggregation, which is impractical under the limited connectivity, privacy concerns, and resource…
  openalex Alexandros Kalafatelis, Angeliki Pitsiakou, Νικόλαος Νομικός, Nikolaos Tsoulakos 等 2025-08-15 置信度 0.84 PruningDistillationComputer sciencePredictive maintenanceMachine learning
• Federated Learning and Blockchain Framework for Scalable and Secure IoT Access Control
  The increasing deployment of Internet of Things (IoT) devices has introduced significant security challenges, including identity spoofing, unauthorized access, and data integrity breaches. Traditional security mechanisms rely... | Find, read and cite all the r…
  openalex Ammar Odeh, Anas Abu Taleb 2025-01-01 置信度 0.82 BlockchainScalabilityInternet of ThingsComputer scienceAccess control
• Latency Analysis of UAV-Assisted Vehicular Communications Using Personalized Federated Learning with Attention Mechanism
  In this paper, unmanned aerial vehicle (UAV)-assisted vehicular communications are investigated to minimize latency and maximize the utilization of available UAV battery power. As communication and cooperation among UAV and vehicles is frequently required, a v…
  openalex Abhishek Gupta, Xavier Fernando 2025-07-15 置信度 0.84 Latency (audio)Mechanism (biology)Computer scienceComputer networkHuman–computer interaction
• Comparative analysis of deep learning architectures in solar power prediction
  Integrating renewable energy sources into the electricity grid requires accurate forecasts of solar power production. With the aim of enhancing the accuracy and reliability of forecasts, this study presents a comprehensive comparative analysis of eight state-o…
  openalex Montaser Abdelsattar, Mohamed Mostafa A. Azim, Ahmed AbdelMoety, Ahmed Emad-Eldeen 2025-08-28 置信度 0.84 AutoencoderComputer scienceConvolutional neural networkArtificial intelligenceAlgorithm
• A deep learning/machine learning approach for anomaly based network intrusion detection
  Introduction: The increasing complexity and frequency of cybersecurity threats necessitate the development of advanced detection systems capable of identifying both known and emerging attacks. In this study, we present a hybrid anomaly-based Network Intrusion …
  openalex Reem Al-Muhanna, Samia Dardouri 2025-09-09 置信度 0.84 Intrusion detection systemGeneralizability theoryRobustness (evolution)Anomaly detectionComputer science
• Deep learning for sustainable development across climate, energy, agriculture and urban systems
  Deep learning (DL) has emerged as a transformative paradigm for addressing the multidimensional and data-intensive challenges of sustainable development. The purpose of this review is to examine how DL contributes to four critical domains-climate action, susta…
  openalex Harshit Sharma, Simran Kaur 2025-12-22 置信度 0.84 Transformative learningSustainabilitySustainable developmentDeep learningCitizen journalism
• Decentralized AI at the Edge: Federated Learning, Quantum Optimization and IoT Scalability
  Decentralized artificial intelligence (AI) at the edge marks a revolutionary evolution in computing, enabling efficient, privacy-preserving, and scalable solutions tailored for the Internet of Things (IoT). This paper integrates cutting-edge advancements in fe…
  openalex Surya Kiran, Arjun Kumar, Swathi Chukkala 2025-03-10 置信度 0.84 ScalabilityComputer scienceEnhanced Data Rates for GSM EvolutionInternet of ThingsDistributed computing
• A Survey of Clustering Federated Learning in Heterogeneous Data Scenarios
  Federated learning, as a collaborative training paradigm that preserves raw data privacy, offers an effective solution for data protection concerns. However, its practical implementation faces significant challenges due to data heterogeneity. This heterogeneit…
  openalex Entuo Liu, Wentong Yang, Yonggen Gu, Wei Long 等 2025-04-30 置信度 0.84 Cluster analysisComputer scienceData miningData scienceMachine learning
• Resource-Constrained Decentralized Federated Learning via Personalized Event-Triggering
  Federated learning (FL) is a popular technique for distributing machine learning (ML) across a set of edge devices. In this paper, we study fully decentralized FL, where in addition to devices conducting training locally, they carry out model aggregations via …
  openalex Shahryar Zehtabi, Seyyedali Hosseinalipour, Christopher G. Brinton 2022-11-23 置信度 0.82 Asynchronous communicationComputer scienceDistributed computingEnhanced Data Rates for GSM EvolutionConvergence (economics)
• Ultra-Short-Term Distributed Photovoltaic Power Probabilistic Forecasting Method Based on Federated Learning and Joint Probability Distribution Modeling
  The accurate probabilistic forecasting of ultra-short-term power generation from distributed photovoltaic (DPV) systems is of great significance for optimizing electricity markets and managing energy on the user side. Existing methods regarding cluster informa…
  openalex Yübo Wang, Chao Huo, Fei Xu, Libin Zheng 等 2025-01-05 置信度 0.84 Computer scienceProbabilistic logicData miningProbabilistic forecastingJoint probability distribution
• Empowering Federated Graph Rationale Learning with Latent Environments
  The success of Graph Neural Networks (GNNs) in graph classification has heightened interest in explainable GNNs, particularly through graph rationalization. This method aims to enhance GNNs explainability by identifying subgraph structures (i.e., rationales) t…
  openalex Linan Yue, Qi Liu, Yawen Li, Fangzhou Yao 等 2025-04-22 置信度 0.84 Computer scienceGraphData scienceWorld Wide WebTheoretical computer science
• Participant Selection for Efficient and Trusted Federated Learning in Blockchain-Assisted Hierarchical Federated Learning Architectures
  Federated learning has attracted widespread attention due to its strong capabilities of privacy protection, making it a powerful supporting technology for addressing data silos in the future. However, federated learning still lags significantly behind traditio…
  openalex Peng Liu, Lili Jia, Yang Xiao 2025-02-08 置信度 0.84 BlockchainComputer scienceFederated learningSelection (genetic algorithm)Direct Anonymous Attestation
• Privacy-Preserving Federated Learning for Predictive Maintenance in Smart Manufacturing Networks
  Smart manufacturing environments (digitalized production systems with integrated sensor networks and data analytics capabilities) require advanced predictive maintenance capabilities, yet implementation faces significant barriers due to data privacy concerns a…
  openalex Yulineth Cárdenas Escorcia, Sardor Sabirov, Bakhodir Saydullayev, A. V. Umarov 等 2025-09-08 置信度 0.84 Predictive maintenanceComputer scienceOverhead (engineering)Predictive analyticsDifferential privacy
• HtFLlib: A Comprehensive Heterogeneous Federated Learning Library and Benchmark
  As AI evolves, collaboration among heterogeneous models helps overcome data scarcity by enabling knowledge transfer across institutions and devices.Traditional Federated Learning (FL) only supports homogeneous models, limiting collaboration among clients with …
  openalex Jianqing Zhang, Xinghao Wu, Yanbing Zhou, Xiaoting Sun 等 2025-08-03 置信度 0.84 Benchmark (surveying)Computer scienceArtificial intelligenceData scienceInformation retrieval
• Quantization-based chained privacy-preserving federated learning
  Federated Learning (FL) is an advanced distributed machine learning framework crucial in protecting data privacy and security. By enabling multiple participants to train models while keeping their data local collaboratively, FL effectively mitigates the risks …
  openalex Ya Liu, Shumin Wu, Yibo Li, Fengyu Zhao 等 2025-05-16 置信度 0.84 Computer scienceFederated learningQuantization (signal processing)World Wide WebInternet privacy
• Federated Learning Approaches for Privacy-Preserving Threat Detection in Smart Home IoT Environments
  Smart home Internet of Things (IoT) environments have become increasingly pervasive, offering convenience and automation while simultaneously introducing new cybersecurity vulnerabilities. Traditional centralized machine learning approaches for threat detectio…
  openalex Chima Nwankwo Idika, Edward Oziegbe Salami 2024-10-30 置信度 0.84 Internet of ThingsInternet privacyComputer securityHome automationComputer science
• Federated Learning for Semantic Communication Based on CNNs and Transformer
  This study focuses on the latest research advancements in the field of semantic communication. Traditional communication systems prioritize the transmission of raw data, whilst semantic communication emphasizes conveying the meaning represented by the data. Ho…
  openalex Shufeng Li, Yujun Cai, Zhaokai Deng, Xinran Ba 等 2025-01-01 置信度 0.84 Computer scienceTransformerConvolutional neural networkArtificial intelligenceSemantic data model
• Federated Multi-Agent DRL for Task Offloading in Vehicular Edge Computing
  With the expansion of vehicle-to-everything (V2X) networks and the rising demand for intelligent services, vehicle edge computing encounters heightened requirements for more efficient task offloading. This study proposes a task offloading technique that utiliz…
  openalex Hongwei Zhao, Yu Li, Zhixi Pang, Zihan Ma 2025-09-01 置信度 0.84 Computer scienceEdge computingTask (project management)Enhanced Data Rates for GSM EvolutionDistributed computing
• Privacy and Trust in Blockchain-Federated Intrusion Detection Systems: Taxonomy, Challenges and Perspectives
  Intrusion Detection Systems (IDS) play a critical role in protecting modern networks, but traditional centralized designs raise serious concerns regarding data privacy, trust, and scalability. Federated Learning (FL) reduces privacy risks through decentralized…
  openalex Cao Yuan, Chin Soon Ku, Rahul Kumar, Arshad Khan 2025-11-02 置信度 0.84 Computer scienceImmutabilityComputer securityTrustworthinessKey (lock)
• FedSteg: Coverless Steganography‐Based Privacy‐Preserving Decentralized Federated Learning
  Federated learning (FL) represents a novel privacy‐preserving learning paradigm that offers a practical solution for distributed privacy preservation. Although privacy‐preserving FL based on homomorphic encryption (HE‐PPFL) exhibits resistance to gradient leak…
  openalex Mengfan Xu, Yaguang Lin 2024-04-29 置信度 0.84 SteganographyComputer scienceBlockchainSteganography toolsComputer security
• Managing Supply and Value Chains in a New Era of Global Trade: The Promise of Federated Learning
  As global trade shifts from an era of efficiency-driven globalisation to a new compliance-centred paradigm, customs administrations face mounting challenges – ranging from forced labour and environmental enforcement to fractured supply chain visibility and esc…
  openalex Alan Bersin, Peter Goodings Swartz, Lars Karlsson 2025-04-29 置信度 0.84 Supply chainValue (mathematics)BusinessInternational tradeComputer science
• Advancements and Challenges in Federated Learning : A Survey
  Machine Learning (ML) has significantly impacted daily life by automating tasks and enhancing decision-making across diverse sectors such as healthcare, finance, and transportation. However, concerns regarding data privacy, particularly in sensitive domains li…
  openalex Vivek Prajapat, Narendra Pal Singh Rathore, Kamal Kumar Sethi, Shiv Shankar Rajput 2024-09-27 置信度 0.82 Computer scienceData science
• HealthGuard: An Intelligent Healthcare System Security Framework Based on Machine Learning
  Utilization of the Internet of Things and ubiquitous computing in medical apparatuses have “smartified” the current healthcare system. These days, healthcare is used for more than simply curing patients. A Smart Healthcare System (SHS) is a network of implante…
  openalex Amit Sundas, Sumit Badotra, Salil Bharany, Ahmad Almogren 等 2022-09-22 置信度 0.82 Computer scienceWearable computerComputer securityInternet of ThingsWearable technology
• Federated Low-Rank Adaptation for Foundation Models: A Survey
  Effectively leveraging private datasets remains a significant challenge in developing foundation models. Federated Learning (FL) has recently emerged as a collaborative framework that enables multiple users to fine-tune these models while mitigating data priva…
  openalex Yiyuan Yang, Guodong Long, Qinghua Lu, Liming Zhu 等 2025-09-01 置信度 0.84 Foundation (evidence)Computer scienceAdaptation (eye)Data scienceKey (lock)
• Integrating reinforcement learning and federated meta-learning for energy-efficient wireless body sensor networks
  Abstract Intra wireless body sensor network (Intra-WBSN) is typically a short range wireless health monitoring network, Intra wireless body sensor network (Intra-WBSN) is typically a short range wireless health monitoring network, Wireless body sensor networks…
  openalex Soufiane Ben Othman 2025-12-01 置信度 0.84 Computer scienceWireless sensor networkComputer networkKey distribution in wireless sensor networksDistributed computing
• Machine Learning for Service Migration: A Survey
  Future communication networks are envisioned to satisfy increasingly granular and dynamic requirements to accommodate the application and user demands. Indeed, novel immersive and mission-critical services necessitate increased computing and network resources,…
  openalex Nassima Toumi, Miloud Bagaa, Adlen Ksentini 2023-01-01 置信度 0.82 Computer scienceOrchestrationService (business)EnablingQuality of service
• Artificial intelligence and students’ cognitive learning outcomes with bibliometric and content analysis for future research agenda
  This study conducted a comprehensive bibliometric and content analysis to explore the integration of artificial intelligence in students’ cognitive learning outcomes. A structured TITLE-ABS-KEY search was performed in the Scopus database using keywords such as…
  openalex Shaukat Rahman Ansari, Ika Nurul Qamari 2025-10-21 置信度 0.84 Transformative learningContent analysisScopusBibliometricsComputer science
• Framework for Addressing Imbalanced Data in Aviation with Federated Learning
  The aviation industry generates vast amounts of data across multiple stakeholders, but critical faults and anomalies occur rarely, creating inherently imbalanced datasets that complicate machine learning applications. Traditional centralized approaches are fur…
  openalex Igor Kabashkin 2025-02-16 置信度 0.84 AviationData scienceComputer scienceKnowledge managementEngineering
• FedMDKGE: Multi-granularity Dynamic Knowledge Graph Embedding in Federated Learning
  As knowledge is time-sensitive, some researchers have started to focus on dynamic knowledge graphs to provide time-dimensioned knowledge content thus reflecting richer information. But they have not yet combined temporal information at different granularities.…
  openalex Wei Huang, Junling Chen, Dexian Wang, Pengfei Zhang 等 2025-06-02 置信度 0.84 GranularityComputer scienceEmbeddingKnowledge graphGraph
• Towards a robust, effective and resource efficient machine learning technique for IoT security monitoring
  The application of Deep Neural Networks (DNNs) for monitoring cyberattacks in Internet of Things (IoT) systems has gained significant attention in recent years. However, achieving optimal detection performance through DNN training has posed challenges due to c…
  openalex Idris Zakariyya, Harsha Kalutarage, M. Omar Al-Kadri 2023-07-20 置信度 0.82 Computer scienceTestbedRobustness (evolution)Artificial intelligenceMemory footprint
• Model Poisoning Attacks to Federated Learning via Multi-Round Consistency
  Model poisoning attacks are critical security threats to Federated Learning (FL). Existing model poisoning attacks suffer from two key limitations: 1) they achieve suboptimal effectiveness when defenses are deployed, and/or 2) they require knowledge of the mod…
  openalex Yueqi Xie, Minghong Fang, Neil Zhenqiang Gong 2024-04-24 置信度 0.84 Consistency (knowledge bases)Computer scienceComputer securityFederated learningDatabase
• Federated Learning for Multi-Disease Ophthalmic Diagnostics Using OCT Angiography
  Purpose: To conduct a comprehensive systematic evaluation of federated learning (FL) strategies for multi-disease retinal classification using OCT angiography (OCTA), implementing a 2-part experimental framework to establish foundational feasibility and optimi…
  openalex Ahammed Sakir Nabil, Sina Gholami, Theodore Leng, Jennifer I. Lim 等 2025-12-19 置信度 0.84 MedicineComputer scienceAngiographyComputer visionArtificial intelligence
• Federated Deep Reinforcement Learning for Privacy-Preserving Robotic-Assisted Surgery
  The integration of Reinforcement Learning (RL) into robotic-assisted surgery (RAS) holds significant promise for advancing surgical precision, adaptability, and autonomous decision-making. However, the development of robust RL models in clinical settings is hi…
  openalex Sana Hafeez, Sundas Rafat Mulkana, Muhammad Ali Imran, Michele Sevegnani 2025-07-21 置信度 0.84 Reinforcement learningComputer scienceHomomorphic encryptionSoftware deploymentMargin (machine learning)
• Personalized Federated Transfer Learning for Building Energy Forecasting via Model Ensemble with Multi-Level Masking in Heterogeneous Sensing Environment
  Effective building energy prediction is essential for optimizing energy management, but existing models struggle with data scarcity and sensor heterogeneity across different buildings. Conventional approaches, including centralized and transfer learning method…
  openalex Hakjae Kim, Sarangerel Dorjgochoo, Hansaem Park, Sung-Ju Lee 2025-04-28 置信度 0.84 Computer scienceMasking (illustration)Transfer of learningEnergy transferFederated learning
• Artificial Intelligence and machine learning in fraud detection for digital payments
  The financial sector has adopted artificial intelligence (AI) and machine learning (ML) for more advanced and real-time fraud detection as a result of the increased threat of fraud brought on by the global surge in digital payments. By using sophisticated algo…
  openalex Alexandre Davitaia 2025-06-13 置信度 0.84 PaymentComputer scienceArtificial intelligenceMachine learningComputer security
• Linking Health Records for Federated Query Processing
  Abstract A federated query portal in an electronic health record infrastructure enables large epidemiology studies by combining data from geographically dispersed medical institutions. However, an individual’s health record has been found to be distributed acr…
  openalex Rinku Dewri, Toan C. Ong, Ramakrishna Thurimella 2016-05-06 置信度 0.80 Computer scienceIdentifierEncryptionInformation retrievalSet (abstract data type)
• Federated Deep Learning for Robust Multi-Modal Biometric Authentication Based on Facial and Eye-Blink Cues
  The increasing demand for secure and user-friendly authentication mechanisms has led to the exploration of biometric systems that leverage unique physiological traits. Among these, face recognition and eye blink detection have emerged as effective and non-intr…
  openalex A. Balaji, Doppalapudi Balanjali, Guntu Subbaiah, Avula Anil Reddy 等 2025-04-14 置信度 0.84 BiometricsComputer scienceSpoofing attackLeverage (statistics)Facial recognition system
• On-Device Federated Learning for Energy-Efficient Smart Irrigation
  This study presents a novel federated learning (FL) methodology implemented directly on STM32-based microcontrollers (MCUs) for energy-efficient smart irrigation. To the best of our knowledge, this is the first work to demonstrate end-to-end FL training and ag…
  openalex Zohra Dakhia, Alessia Lazzaro, Mohamed Riad Sebti, Mariateresa Russo 等 2025-11-02 置信度 0.84 MicrocontrollerComputer scienceMessage queueInferenceSecurity token
• Collision avoidance in UAV swarms: A learning-centric perspective on collaborative intelligence
  As UAV swarm deployments become more prevalent in mission critical domains, collision avoidance remains a key challenge in ensuring safety, coordination, and autonomy at scale. This survey investigates the state of the art in learning based collision avoidance…
  openalex Himadri Sikhar Khargharia, Anis Ouali, Siddhartha Shakya, S. Ahmad 2025-11-08 置信度 0.84 Computer scienceCollision avoidanceSoftware deploymentReinforcement learningScalability
• Review: machine learning approaches for diverse alloy systems
  Abstract The integration of machine learning (ML) into alloy design has revolutionized the discovery and optimization of advanced materials by enabling high-throughput, data-driven methodologies. This review systematically examines recent advancements in ML ap…
  openalex Arafat Rahman, Md Sojib Hossain, Abdullah Siddique 2025-07-17 置信度 0.84 Materials scienceSolid mechanicsAlloyMetallurgyPolymer science
• Federated transfer learning for distributed drought stage prediction
  Abstract Due to the uncertain nature of drought, it is one of the most menacing natural disasters. Drought modeling (Prediction, Detection, Forecasting, and Stage Prediction) is very essential for efficient policy making. But one of the key problems with droug…
  openalex Muhammad Owais Raza, Aqsa Umar, Jawad Rasheed, Tunç Aşuroğlu 等 2025-05-11 置信度 0.84 Transfer of learningStage (stratigraphy)Computer scienceTransfer (computing)Artificial intelligence
• RUL Prediction of Lithium-ion Batteries using a Federated and Homomorphically Encrypted Learning Method
  The increasing demand for lithium-ion batteries (LIB) across various industries has accentuated the importance of accurately predicting the Remaining Useful Life (RUL) of these energy storage devices. This article introduces a novel approach to RUL prediction …
  openalex Víctor López, Óscar Fontenla-Romero, Elena Hernández-Pereira, Bertha Guijarro‐Berdiñas 等 2024-04-08 置信度 0.84 Lithium (medication)IonComputer scienceMaterials scienceComputational science
• Federated LeViT-ResUNet for Scalable and Privacy-Preserving Agricultural Monitoring Using Drone and Internet of Things Data
  Precision agriculture is necessary for dealing with problems like pest outbreaks, a lack of water, and declining crop health. Manual inspections and broad-spectrum pesticide application are inefficient, time-consuming, and dangerous. New drone photography and …
  openalex Mohammad Aldossary, Jaber Almutairi, Ibrahim Alzamil 2025-04-10 置信度 0.84 DroneInternet of ThingsScalabilityComputer scienceInternet privacy
• Dual prompt personalized federated learning in foundation models
  Personalized federated learning (PFL) has garnered significant attention for its ability to address heterogeneous client data distributions while preserving data privacy. However, when local client data is limited, deep learning models often suffer from insuff…
  openalex Ying Chang, Xiaohu Shi, Zhao Xiaohui, Zhaohuang Chen 等 2025-07-31 置信度 0.84 Foundation (evidence)Computer scienceFederated learningDual (grammatical number)Data science
• Secure and Differentially Private Edge-Cloud Federated Learning Framework for Privacy-Preserving Maritime AIS Intelligence
  Cloud computing now supports large-scale maritime analytics, yet offloading rich Automatic Identification System (AIS) data to the cloud exposes sensitive operational patterns and complicates compliance with cross-border priv... | Find, read and cite all the r…
  openalex Abuzar Khan, Abid Iqbal, Ghassan Husnain, Fahad Masood 等 2026-01-01 置信度 0.82 Computer scienceCloud computingPayload (computing)Differential privacyHomomorphic encryption
• Design of an Immersive Basketball Tactical Training System Based on Digital Twins and Federated Learning
  To address the challenges of dynamic adversarial scenario modeling distortion, insufficient cross-institutional data privacy protection, and simplistic evaluation systems in collegiate basketball tactical education, this study proposes and validates an immersi…
  openalex Xiongce Lv, Ye Tao, Yifan Zhang, Yang Xue 2025-03-31 置信度 0.84 BasketballComputer scienceTraining (meteorology)MultimediaHuman–computer interaction
• Federated Incentive Learning: A Privacy-Preserving Framework for Ad Monetization and Creator Rewards in High-Concurrency Environments
  Growing regulatory pressures have upended the historical pattern of cross-site behavioral targeting and measurement, forcing ad monetization systems to reconcile personalization, creator incentives, and privacy by design. This paper introduces Federated Incent…
  openalex Xun Yi 2025-10-13 置信度 0.84 MonetizationIncentiveComputer scienceSandbox (software development)Earnings
• Deep Learning in Human Activity Recognition with Wearable Sensors: A Review on Advances
  Mobile and wearable devices have enabled numerous applications, including activity tracking, wellness monitoring, and human--computer interaction, that measure and improve our daily lives. Many of these applications are made possible by leveraging the rich col…
  openalex Shibo Zhang, Yaxuan Li, Shen Zhang, Farzad Shahabi 等 2021-10-31 置信度 0.78 Wearable computerComputer scienceDeep learningWearable technologyActivity recognition
• The role of explainable AI in enhancing breast cancer diagnosis using machine learning and deep learning models
  Breast cancer is still a big health issue around the world, and it needs to be found quickly and perfectly to improve patient outcomes and lower death rates. Although artificial intelligence (AI) has showed amazing promise in breast cancer prediction mainly ma…
  openalex Zulfikar Ali Ansari, Manish Madhava Tripathi, Rafeeq Ahmed 2025-05-26 置信度 0.84 Artificial intelligenceBreast cancerComputer scienceDeep learningCancer
• Ensuring Zero Trust in GDPR-Compliant Deep Federated Learning Architecture
  Deep Federated Learning (DFL) revolutionizes machine learning (ML) by enabling collaborative model training across diverse, decentralized data sources without direct data sharing, emphasizing user privacy and data sovereignty. Despite its potential, DFL’s appl…
  openalex Zahra Abbas, Sunila Fatima Ahmad, Adeel Anjum, Madiha Haider Syed 等 2025-08-04 置信度 0.84 ArchitectureZero (linguistics)Computer scienceComputer securityBusiness
• Federated Learning with Pareto Optimality for Resource Efficiency and Fast Model Convergence in Mobile Environments
  Federated learning (FL) is an emerging distributed learning technique through which models can be trained using the data collected by user devices in resource-constrained situations while protecting user privacy. However, FL has three main limitations: First, …
  openalex June-Pyo Jung, Young‐Bae Ko, Sung‐Hwa Lim 2024-04-12 置信度 0.84 Computer scienceCluster analysisConvergence (economics)Pareto principleScheme (mathematics)
• Pediatric ECG-Based Deep Learning to Predict Left Ventricular Dysfunction and Remodeling
  BACKGROUND: Artificial intelligence-enhanced ECG analysis shows promise to detect ventricular dysfunction and remodeling in adult populations. However, its application to pediatric populations remains underexplored. METHODS: A convolutional neural network was …
  openalex Joshua Mayourian, William La Cava, Akhil Vaid, Girish N. Nadkarni 等 2024-02-05 置信度 0.84 MedicineReceiver operating characteristicLeft ventricular hypertrophyInternal medicineCardiology
• Towards Secure and Efficient Farming Using Self-Regulating Heterogeneous Federated Learning in Dynamic Network Conditions
  The advancement of precision agriculture increasingly depends on innovative technological solutions that optimize resource utilization and minimize environmental impact. This paper introduces a novel heterogeneous federated learning architecture specifically d…
  openalex Sai Puppala, Koushik Sinha 2025-04-25 置信度 0.84 AgricultureComputer scienceBusinessComputer networkBiology
• Practical Federated Learning without a Server
  Federated Learning (FL) enables end-user devices to collaboratively train ML models without sharing raw data, thereby preserving data privacy. In FL, a central parameter server coordinates the learning process by iteratively aggregating the trained models rece…
  openalex Akash Dhasade, Anne-Marie Kermarrec, Erick Lavoie, Johan Pouwelse 等 2025-03-30 置信度 0.82 Computer scienceWorld Wide Web
• Intelligent waste sorting for urban sustainability using deep learning
  Smart cities’ have experienced an increasingly higher rate of urbanization and increase of the population leading to strengthening the pressing needs in waste management. In this paper, we present an intelligent waste classification system that utilises Convol…
  openalex G.F. Ahmad, Fizza Muhammad Aleem, Tahir Alyas, Qaiser Abbas 等 2025-07-25 置信度 0.84 SustainabilitySortingComputer scienceUrban sustainabilityDeep learning
• AnoFel: Supporting Anonymity for Privacy-Preserving Federated Learning
  Federated learning enables users to collaboratively train a machine learning model over their private datasets. Secure aggregation protocols are employed to mitigate information leakage about the local datasets from user-submitted model updates. This setup, ho…
  openalex Ghada Almashaqbeh, Zahra Ghodsi 2025-03-07 置信度 0.84 AnonymityInternet privacyComputer scienceComputer securityFederated learning
• Deep learning for intrusion detection in emerging technologies: a comprehensive survey and new perspectives
  Abstract Intrusion Detection Systems (IDS) can help cybersecurity analysts detect malicious activities in computational environments. Recently, Deep Learning (DL) methods in IDS have demonstrated notable performance, revealing new underlying cybersecurity patt…
  openalex Euclides Carlos Pinto Neto, Shahrear Iqbal, Scott Buffett, Madeena Sultana 等 2025-08-20 置信度 0.84 Computer scienceIntrusion detection systemDeep learningData scienceEmerging technologies
• Federated learning for the pathogenicity annotation of genetic variants in multi-site clinical settings
  MOTIVATION: Rare diseases collectively affect 5% of the population. However, fewer than 50% of rare disease patients receive a molecular diagnosis after whole genome sequencing. Supervised machine learning is a valuable approach for the pathogenicity scoring o…
  openalex Nigreisy Montalvo, Francisco Requena Silvente, Emidio Capriotti, Antonio Rausell 2025-09-19 置信度 0.84 Genetic variantsAnnotationPathogenicityComputer scienceLicense
• Blockchain-based federated learning framework for malicious node detection in internet of vehicles (IoV) networks using fog and cloud computing
  Due to the continuous digitalization, IoV networks are vulnerable to various communication attacks by malicious network nodes. In these attacks, the malicious entities disseminate faulty information in the network, which affects quick and intelligent decision-…
  openalex Srinivas Reddy Bandarapu, Muhammad Bilal, Pushpalika Chatterjee, Adnan Mustafa Cheema 等 2025-07-21 置信度 0.84 BlockchainCloud computingComputer scienceNode (physics)The Internet
• Realistic Urban Traffic Generator Using Decentralized Federated Learning for the SUMO Simulator
  Realistic urban traffic simulation is essential for sustainable urban planning and the development of intelligent transportation systems. However, generating high-fidelity, time-varying traffic profiles that accurately reflect real-world conditions, especially…
  openalex Alberto Bazán-Guillén, Carlos Beis-Penedo, Diego Cajaraville-Aboy, Pablo Barbecho Bautista 等 2025-01-01 置信度 0.84 Generator (circuit theory)Computer scienceSimulationTransport engineeringEngineering
• A review of security threats and privacy issues in federated learning
  openalex Abhishek Kumar Agrahari, Aarti Gautam Dinker, Rajendra Bahadur Singh 2026-03-02 置信度 0.73 Computer scienceAdversarial systemComputer securityBackdoorFederated learning
• Federated Learning with Adversarial Optimisation for Secure and Efficient 5G Edge Computing Networks
  With the evolution of 5G edge computing networks, privacy-aware applications are gaining significant attention due to their decentralised processing capabilities. However, these networks face substantial challenges to ensure privacy and security, specifically …
  openalex Saniya Zafar, Jonathan White, Phil Legg 2025-09-17 置信度 0.84 Adversarial systemComputer scienceAdversaryRobustness (evolution)Edge computing
• Federated Learning for Privacy-Preserving Apparel Supply Chain Analytics
  The apparel industry operates through highly complex and globalized supply chains, where effective data analytics plays a critical role in improving demand forecasting, inventory management, logistics coordination, and sustainability practices. However, organi…
  openalex Mizanur Rahman, Samsul Haque, S M Arif Al Sany 2025-10-16 置信度 0.84 Supply chainAnalyticsComputer scienceBig dataSustainability
• Federated Learning for Medical Image Analysis: Privacy-Preserving Paradigms and Clinical Challenges
  Federated Learning (FL) has emerged as a transformative paradigm in medical image analysis, addressing the critical challenges of data scarcity and patient privacy. By enabling collaborative model training across decentralized datasets without requiring data s…
  openalex Juntao Hu, Zhengjie Yang, Peng Wang, Guanyi Zhao 等 2025-08-11 置信度 0.84 Computer scienceImage (mathematics)Internet privacyData scienceArtificial intelligence
• Federated Learning for Early Cardiac Anomaly Prediction in Cross-Silo IoMT Environments
  Early detection of cardiovascular anomalies remains critical for proactive patient care, especially within the growing ecosystem of Internet of Medical Things (IoMT) devices. This study explores the application of Federated Learning (FL) to predict early cardi…
  openalex Michael Georgiades, Lakis Christodoulou, Andreas Chari, Kezhi Wang 等 2025-06-09 置信度 0.84 SiloComputer scienceAnomaly (physics)Anomaly detectionArtificial intelligence
• Federated Learning-Based Intrusion Detection Framework for Internet of Things and Edge Computing Backed Critical Infrastructure
  Modern Critical Infrastructure (CI) sectors including Smart Girds operate on the Internet of Things and edge computing paradigm. With the enormous growth of these sectors, there are emerging and escalating cyber threats. Traditional Machine Mearning (ML) appro…
  openalex Ruofei Meng, Awais Aziz Shah, Muhammad Ali Jamshed, Dimitrios P. Pezaros 2024-06-09 置信度 0.84 Computer scienceEdge computingInternet of ThingsCritical infrastructureEnhanced Data Rates for GSM Evolution
• An optimized oversampling-based federated transfer learning approach for rotating machinery cluster fault diagnosis
  Abstract With the development of distributed industrial systems, rotating machinery as the core power and transmission unit of complex distributed industrial systems, its fault diagnosis is very necessary and faces the serious challenge of Non-Independent and …
  openalex Zhao Xu, Liya Yu, Shaobo Li, Chuanjiang Li 等 2025-07-23 置信度 0.84 OversamplingFault (geology)Cluster (spacecraft)Transfer of learningComputer science
• AI-Driven Privacy Shield: A Secure and Privacy-Preserving Federated Learning Framework
  Emerging, highly skilled cyberattacks demand novel and robust techniques for AI-powered privacy preservation. Centralized machine learning models can be compromised with a single point of failure, a data breach, or an adversarial attack. The proposed work pres…
  openalex Yasir M. Abdal 2025-09-07 置信度 0.84 Computer scienceFederated learningAdversarial systemScalabilityEncryption
• Evaluating machine learning algorithms for energy consumption prediction in electric vehicles: A comparative study
  An accurate energy consumption prediction becomes crucial with increasing electric vehicle usage for effective power grid management. This research examined the performance of eleven machine learning models for this purpose: Ridge Regression, Lasso Regression,…
  openalex Izhar Hussain, Kok Boon Ching, Chessda Uttraphan, Kim Gaik Tay 等 2025-05-08 置信度 0.84 Computer scienceEnergy consumptionMachine learningEnergy (signal processing)Artificial intelligence
• Privacy-Preserving Generative AI in Healthcare Systems Using Federated Learning Approaches
  The research paper focuses on the mechanism of introducing Federated Learning alongside privacy-saving strategies in Generative Artificial Intelligence to healthcare applications. The study analyses the privacy protection/model accuracy trade-off by implementi…
  openalex Rajesh A. Poojari 2026-02-28 置信度 0.84 Federated learningComputer scienceDifferential privacyGenerative grammarArtificial intelligence
• SplitML: A Unified Privacy-Preserving Architecture for Federated Split-Learning in Heterogeneous Environments
  While Federated Learning (FL) and Split Learning (SL) aim to uphold data confidentiality by localized training, they remain susceptible to adversarial threats such as model poisoning and sophisticated inference attacks. To mitigate these vulnerabilities, we pr…
  openalex Devharsh Trivedi, Aymen Boudguiga, Nesrine Kaaniche, Nikos Triandopoulos 2026-01-07 置信度 0.84 Federated learningInferenceComputer scienceHomomorphic encryptionConfidentiality
• Toward intelligent and resilient microgrids: A survey of machine learning approaches for renewable energy integration
  openalex Darioush Razmi, Peyman Razmi, Oluleke Babayomi, Zhenbin Zhang 2026-04-24 置信度 0.73 Renewable energyComputer scienceArtificial intelligenceMachine learningEnergy (signal processing)
• FedCVG: a two-stage robust federated learning optimization algorithm
  Federated learning provides an effective solution to the data privacy issue in distributed machine learning. However, distributed federated learning systems are inherently susceptible to data poisoning attacks and data heterogeneity. Under conditions of high d…
  openalex Runze Zhang, Yang Zhang, Yating Zhao, Bin Jia 等 2025-05-26 置信度 0.84 Computer scienceStage (stratigraphy)Optimization algorithmAlgorithmArtificial intelligence
• A Survey on Federated Learning in Human Sensing
  Human Sensing, a field that leverages technology to monitor human activities, psycho-physiological states, and interactions with the environment, enhances our understanding of human behavior and drives the development of advanced services that improve overall …
  openalex Mohan Li, Martin Gjoreski, Pietro Barbiero, Gašper Slapničar 等 2025-01-07 置信度 0.84 Computer scienceData scienceHuman–computer interaction
• Strategies to Improve the Robustness and Generalizability of Deep Learning Segmentation and Classification in Neuroimaging
  Artificial Intelligence (AI) and deep learning models have revolutionized diagnosis, prognostication, and treatment planning by extracting complex patterns from medical images, enabling more accurate, personalized, and timely clinical decisions. Despite its pr…
  openalex Anh T. Tran, Tal Zeevi, Seyedmehdi Payabvash 2025-04-14 置信度 0.84 Generalizability theoryArtificial intelligenceComputer scienceNeuroimagingRobustness (evolution)
• A systematic literature review on federated cyber-attack detection for edge intelligence: Challenges, approaches, and future directions
  The rapid expansion of Edge Computing (EC) and Internet of Things devices has introduced significant cybersecurity challenges, necessitating advanced and privacy-preserving attack detection strategies. Traditional cyber-attack detection methods and centralized…
  openalex Zeseya Sharmin, Md Palash Uddin, Yong Xiang, Feifei Chen 2026-03-20 置信度 0.84 Computer scienceSystematic reviewEnhanced Data Rates for GSM EvolutionInformation retrievalData science
• Robust aggregation algorithms for federated learning in unreliable network environments
  Federated learning (FL) allows joint model training on distributed devices without losing data locality, but its results are significantly worse in unreliable network systems where packets are dropped, clients fail, resources are heterogeneous, and adversarial…
  openalex Ziyang Zeng, Shiyu Yang, Guanyu Ding 2025-10-30 置信度 0.84 Computer scienceNetwork packetOutlierOverhead (engineering)Resilience (materials science)
• Digital Twins: State of the art theory and practice, challenges, and open research questions
  Digital Twin was introduced over a decade ago, as an innovative all-encompassing tool, with perceived benefits including real-time monitoring, simulation, optimisation and accurate forecasting. However, the theoretical framework and practical implementations o…
  openalex Angira Sharma, Edward Elson Kosasih, Jie Zhang, Alexandra Brintrup 等 2022-08-08 置信度 0.82 ImplementationComputer scienceField (mathematics)Key (lock)Data science
• Client to Server: Heterogeneous Distribution Knowledge Transfer for Federated Learning
  Federated learning (FL) is an emerging distributed machine learning paradigm that provides privacy guarantees for training robust models on distributed clients. The primary challenge of FL is data heterogeneity,which slows down model convergence and degrades m…
  openalex Rui Zhao, Xiao Yang, Peng Zhi, Zhihe Zhang 等 2025-08-05 置信度 0.84 Computer scienceDistribution (mathematics)Transfer (computing)Transfer of learningKnowledge transfer
• Towards Trustworthy Machine Learning in Production: An Overview of the Robustness in MLOps Approach
  Artificial intelligence (AI), and especially its sub-field of Machine Learning (ML), are impacting the daily lives of everyone with their ubiquitous applications. In recent years, AI researchers and practitioners have introduced principles and guidelines to bu…
  openalex Firas Bayram, Bestoun S. Ahmed 2024-12-18 置信度 0.84 Computer scienceTrustworthinessRobustness (evolution)Artificial intelligenceMachine learning
• DataSHIELD: mitigating disclosure risk in a multi-site federated analysis platform
  Motivation: The validity of epidemiologic findings can be increased using triangulation, i.e. comparison of findings across contexts, and by having sufficiently large amounts of relevant data to analyse. However, access to data is often constrained by practica…
  openalex Demetris Avraam, Rebecca Wilson, Noemi Aguirre Chan, Soumya Banerjee 等 2024-12-26 置信度 0.80 Computer scienceBusinessRisk analysis (engineering)
• A hybrid machine learning model for intrusion detection in wireless sensor networks leveraging data balancing and dimensionality reduction
  Intrusion detection systems are essential for securing wireless sensor networks (WSNs) and Internet of Things (IoT) environments against various threats. This study presents a novel hybrid machine learning (ML) model that integrates KMeans-SMOTE (KMS) for data…
  openalex Md. Alamin Talukder, Majdi Khalid, Nasrin Sultana 2025-02-07 置信度 0.84 Dimensionality reductionComputer scienceIntrusion detection systemReduction (mathematics)Machine learning
• Federated learning for privacy-preserving AI in human–robot collaboration for smart manufacturing
  Purpose The study aims to address privacy and security challenges in AI-driven human–robot collaboration (HRC) by developing a privacy-preserving federated learning framework. Traditional centralized AI models expose sensitive manufacturing data to cybersecuri…
  openalex Milad Rahmati 2025-04-21 置信度 0.84 Computer scienceRobotHuman–computer interactionHuman–robot interactionInternet privacy
• ZTID-IoV: Zero-Trust Intrusion Detection in IoV Using Neurosymbolic AI Approach With Federated Meta-Learning
  The rapid growth of the Internet of Vehicles (IoVs) and smart consumer electronics has generated cybersecurity concerns that require an intelligent, adaptable, and privacy-preserving Intrusion Detection System (IDS). This study introduces ZTID-IoV, a novel neu…
  openalex Farhan Ullah, Gautam Srivastava, Leonardo Mostarda, Umar Raza 2025-10-23 置信度 0.84 Computer scienceIntrusion detection systemCluster analysisTransparency (behavior)Transformer
• Using Homomorphic Proxy Re‐Encryption to Enhance Security and Privacy of Federated Learning‐Based Intelligent Connected Vehicles
  Intelligent connected vehicles (ICVs) are one of the fast‐growing directions that plays a significant role in the area of autonomous driving. To realize collaborative computation among ICVs, federated learning (FL) or federated‐based large language model (FedL…
  openalex Yang Bai, Y. S. Rao, Hongyan Wu, Juan Wang 等 2025-01-01 置信度 0.84 Homomorphic encryptionComputer scienceProxy (statistics)Computer securityProxy re-encryption
• Lightweight Anomaly Detection in Digit Recognition Using Federated Learning
  This study presents a lightweight autoencoder-based approach for anomaly detection in digit recognition using federated learning on resource-constrained embedded devices. We implement and evaluate compact autoencoder models on the ESP32-CAM microcontroller, en…
  openalex Anja Tanović, Ivan Mezei 2025-07-30 置信度 0.84 AutoencoderComputer scienceMNIST databaseAnomaly detectionInference
• Breakthroughs in Brain Tumor Detection: Leveraging Deep Learning and Transfer Learning for MRI-Based Classification
  Identifying and classifying brain tumors play a pivotal role in gaining insights into their underlying mechanisms. In contemporary medical practice, the integration of Computer-assisted Diagnosis (CAD) and machine learning, particularly deep learning, has sign…
  openalex Alireza Golkarieh, Sajjad Rezvani Boroujeni, Kiana Kiashemshaki, Maryam Deldadehasl 等 2025-07-31 置信度 0.84 Transfer of learningDeep learningComputer scienceArtificial intelligenceMachine learning
• FedEmerge: An Entropy-Guided Federated Learning Method for Sensor Networks and Edge Intelligence
  Introduction: Federated Learning (FL) is a distributed machine learning paradigm where a global model is collaboratively trained across multiple decentralized clients without exchanging raw data. This is especially important in sensor networks and edge intelli…
  openalex Koffka Khan 2025-06-14 置信度 0.84 Computer scienceEnhanced Data Rates for GSM EvolutionEntropy (arrow of time)Artificial intelligenceData science
• RewardChain: A Blockchain-Based Incentive Mechanism for Federated Learning in Consumer-Centric Internet of Medical Things
  Federated learning is a promising approach that enables collaborative machine learning (ML) in distributed environments, such as the Internet of Medical Things (IoMT) while preserving consumer privacy. It allows multiple consumers to collaboratively train a mo…
  openalex Ahmad A Alsharidah, Devki Nandan Jha, Ellis Solaiman, Bo Wei 等 2025-10-27 置信度 0.84 Computer scienceIncentiveProcess (computing)Federated learningBlockchain
• A Multi-View-Based Federated Learning Approach for Intrusion Detection
  Intrusion detection aims to identify the unauthorized activities within computer networks or systems by classifying events into normal or abnormal categories. As modern scenarios often involve multi-source data, multi-view fusion deep learning methods are empl…
  openalex Jia Yu, Guoqiang Wang, Nianfeng Shi, Raghav Saxena 等 2025-10-24 置信度 0.84 Computer scienceIntrusion detection systemRobustness (evolution)AdaptabilityLeverage (statistics)
• Exploiting explanations for model extraction via knowledge distillation and mitigation with private counterfactuals.
  europepmc 2026 置信度 0.72
• The Social Connectedness Index: A large-scale dataset of social ties across geographic locations.
  europepmc 2026 置信度 0.68
• Neurovictimology and the risks of neurotechnologies and artificial intelligence: a forensic and legal perspective.
  europepmc 2026 置信度 0.68
• AI-driven optimization in cloud computing: a systematic review of cost, resource management, and security.
  Cloud computing environments face persistent structural challenges in cost control, dynamic resource allocation, and security risk management, which traditional infrastructure approaches fail to address adequately. This systematic literature review aimed to sy…
  europepmc 2026 置信度 0.94 computer scienceartificial intelligencecloud computingsystematic reviewsustainability
• "In ChatGPT-Powered Virtual Influencers We (Dis)Trust?": The Privacy Paradox and the Double-Edged Sword of Ubiquitous Large Language Model (LLM) Generative AI as a General Purpose Technology (GPT) in a Human-Centered AI Ecosystem.
  europepmc 2026 置信度 0.72
• Harnessing the power of FAIR data to advance sex/gender insights in psychotraumatology.
  europepmc 2026 置信度 0.68
• Research integrity and data ethics in AI-driven integrated healthcare: a critical appraisal.
  The convergence of artificial intelligence (AI) and healthcare is reshaping clinical practice, yet this transformation raises pressing questions about scientific rigor and ethical responsibility. This review provides a critical appraisal of research integrity …
  europepmc 2026 置信度 0.94 engineering ethicshealth caremedicinetransformative learningtransparency
• Machine learning-assisted highly efficient thermal management in function-oriented thermochromic smart windows.
  europepmc 2026 置信度 0.76
• Cross-modal privacy-preserving synthesis and mixture-of-experts ensemble for robust ASD prediction.
  europepmc 2025 置信度 0.76
• Chaotic cosine and logistic map based robust image encryption with dual-stage confusion-diffusion architecture.
  europepmc 2026 置信度 0.72
• Shadow AI in Swedish Health Care: Qualitative Analysis of Physicians' Free-Text Answers.
  europepmc 2026 置信度 0.68
• A privacy preserving synthetic learner dataset for learning analytics in technology enhanced higher education.
  europepmc 2026 置信度 0.76
• The pediatric AI readiness framework: bridging evidence to practice in pediatric artificial intelligence.
  europepmc 2026 置信度 0.68
• Limitations of current copyright frameworks for large language models trained on scientific literature.
  europepmc 2026 置信度 0.68
• AI Applications Integrating Legal and Regulatory Perspectives in Mental Health: Systematic Review.
  europepmc 2026 置信度 0.68
• Blockchain-Based Dynamic and Revocable Consent for Secondary Health Data Use: Systematic Review.
  Background The secondary use of health data holds substantial potential for advancing biomedical research, strengthening population health analytics, and enabling artificial intelligence-driven decision-making support. Yet, ensuring that such reuse respects pa…
  europepmc 2026 置信度 0.94 medicinehealth caredata sciencesystematic reviewbusiness
• Slow Harm After Dobbs v. Jackson Women's Health Organization: An Analytic Scoping Review of How Data and Surveillance Infrastructures Reshape Emergency Obstetric Care.
  europepmc 2026 置信度 0.68
• Editorial: Multimodal brain data integration and computational modeling.
  europepmc 2026 置信度 0.72
• SYNNER synthetic data generator framework.
  europepmc 2026 置信度 0.68
• The 2020 US Decennial Census is more private than you (might) think.
  europepmc 2025 置信度 0.68

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