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• 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