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• Intrusion Detection in the Internet of Things: A Comprehensive Review of Techniques, Architectures, Datasets, and Emerging Trends.
  As the Internet of Things (IoT) grows, strong, scalable, and adaptive intrusion detection systems (IDS) become increasingly critical for protecting IoT environments. This paper presents a comprehensive and systematic survey of IDS techniques for IoT environmen…
  pubmed Komal A, Li S 2026 置信度 0.82
• CRAFT: cold-start recommender with attention and federated training.
  One of the main challenges in recommender systems is the cold-start problem, in which recommendation systems struggle to recommend new or rarely visited items. The traditional methods usually comprise centralized data merging or collaborative filtering techniq…
  pubmed Sivakumar N, John RS, Bijo A, Suganeshwari G 等 2026 置信度 0.82
• Correction: Anomaly detection in double-entry bookkeeping data by federated learning system with non-model sharing approach.
  europepmc 2026 置信度 0.80
• Digital twin driven smart factories: real time physics based co-simulation using edge a.i. and federated learning.
  europepmc 2025 置信度 0.80
• Quantum-Resilient Federated Learning for Multi-Layer Cyber Anomaly Detection in UAV Systems.
  europepmc 2026 置信度 0.80
• Hyperbaric oxygen in the artificial intelligence era: integration and innovation.
  Hyperbaric oxygen therapy is established for decompression illness, carbon monoxide poisoning, radiation-induced tissue injury, and diabetic foot ulcers. Interest in neurological and inflammatory indications is growing, yet outcomes are constrained by heteroge…
  pubmed Epelde F 2026 置信度 0.82
• Rethinking Privacy in Medical Imaging AI: From Metadata and Pixel-Level Identification Risks to Federated Learning and Synthetic Data Challenges.
  pubmed Giouroukou K, Marias K, Tsiknakis M, Klontzas ME 2026 置信度 0.82
• Artificial Intelligence in Digital Banking: A Systematic Literature Review and a Novel Cross-Domain Resilience Framework for Customer Experience, Fraud Detection, and Risk Management
  europepmc 2026 置信度 0.80
• U-FDL-PPE: a unified federated deep learning framework with privacy-preserving explainability for early and accurate viral disease prediction.
  europepmc 2025 置信度 0.80
• Privacy-preserving federated learning with optimized ensemble weighting and knowledge distillation for COVID-19 detection from non-IID medical imaging data.
  Medical imaging enables rapid and accurate diagnosis of COVID-19, with CT scans proving especially effective. However, data privacy concerns limit collaborative model development across hospitals. To address this issue, we introduce a novel federated learning …
  pubmed Annan R, Qin H, Newman R, Siddula M 等 2026 置信度 0.82
• SplitML: A Unified Privacy-Preserving Architecture for Federated Split-Learning in Heterogeneous Environments
  europepmc 2025 置信度 0.80
• Enhancing workplace productivity with secure AI using federated contrastive learning model for performance optimization.
  europepmc 2025 置信度 0.80
• Multi-Modal Data Fusion With Federated Multi-Head Attention for Diabetic Retinopathy Severity Classification
  europepmc 2025 置信度 0.80
• Trustworthy intelligent rooms: integrating blockchain, federated learning, and data-centric AI for healthcare 4.0.
  Intelligent room systems are experiencing a surge in demand within the Healthcare 4.0 ecosystem. The integration of Federated Learning (FL) and Data-Centric AI has led to substantial enhancements in the predictive capabilities of machine learning models while …
  pubmed Veerapaneni RK, Delhibabu R 2026 置信度 0.82
• Federated Learning Architecture for 3D Breast Cancer Image Classification.
  BACKGROUDS: Breast cancer remains a major global health challenge, with early diagnosis playing a crucial role in improving patient survival rates. Among the available diagnostic techniques, mammography is widely employed for early detection. However, its effe…
  europepmc Amel Ali Alhussan, Wiem Nhidi, Imen Filali, Faten Benhmida 等 2025 置信度 0.80 Federated learningComputer scienceBreast cancerArchitectureArtificial intelligence
• Adaptive federated clustering for uncertainty-aware learning on decentralized big data platforms.
  europepmc 2025 置信度 0.80
• Layer-based personalized multi-fusion federated learning.
  europepmc 2025 置信度 0.80
• Artificial Intelligence in the Design and Optimization of Orthodontic Materials: A Clinical Perspective on Current State and Future Directions.
  Artificial intelligence (AI) has transformed orthodontic diagnosis, yet its application to orthodontic materials science remains critically underexplored. This perspective identifies and characterizes the AI-materials integration gap as the central unresolved …
  pubmed Mikulewicz M, Paradowska-Stolarz A 2026 置信度 0.82
• Wireless federated learning for salt-spray prediction in industrial IoT networks with delay constraint.
  europepmc 2025 置信度 0.80
• VQ-FedDiff: Federated Learning Algorithm of Diffusion Models With Client-Specific Vector-Quantized Conditioning.
  europepmc 2025 置信度 0.80
• Federated learning in computational pathology: a literature review.
  pubmed Shukla S, Doyle S 2025 置信度 0.82
• Graph-based federated learning approach for intrusion detection in IoT networks.
  europepmc 2025 置信度 0.80
• Early Tuberculosis Detection via Privacy-Preserving, Adaptive-Weighted Deep Models.
  europepmc 2026 置信度 0.80
• A Privacy-Preserving Approach to Health Insurance Fraud Detection Using Vertical Federated Learning.
  pubmed R RK, Paramarthalingam A, Kanthan H, Karthiban M 2025 置信度 0.82
• Artificial Intelligence Techniques in Blockchain-Integrated Healthcare and Financial Systems: A Systematic Review and Future Research Agenda
  Abstract Blockchain and artificial intelligence (AI) are two innovative technologies that are impacting modern infrastructures with resilience, intelligence, and transparency. Blockchain offers immutability, decentralization, and trust, while AI facilitates de…
  europepmc 2026 置信度 0.80
• DA-PFL: Dynamic Affinity Aggregation in Personalized Federated Learning Under Class Imbalance.
  europepmc 2025 置信度 0.80
• Unveiling Group-Specific Distributed Concept Drift: A Fairness Imperative in Federated Learning.
  europepmc 2026 置信度 0.80
• FedGDAN: Privacy-preserving traffic flow prediction via federated graph diffusion attention networks.
  europepmc 2025 置信度 0.80
• A personalized communication efficient federated learning framework with low rank adaptation for intelligent leukemia diagnosis.
  europepmc 2025 置信度 0.80
• A fully homomorphic encryption federated learning architecture for privacy preserving in industrial internet of things.
  We are currently entering the fifth revolution of industry - Industry 5.0. IIoT is the domain where massive quantities of data are flourished by the associated devices in an industry on a daily basis. To realize industry 4.0, the Industrial internet of things …
  pubmed Subhedar S, Parasar D, Shraddha Subhedar, Deepa Parasar 2026 置信度 0.82
• Information-Theoretic Security and Privacy in Modern Data-Driven Systems.
  europepmc 2026 置信度 0.80
• Distributed Deep Learning in IoT Sensor Network for the Diagnosis of Plant Diseases.
  europepmc 2025 置信度 0.80
• Federated and Quantum-Inspired AI in Adaptive Traffic Systems Using Digital Twin Simulations and Predictive Analytics for Urban Flow Optimization and Carbon Footprint Reduction
  europepmc 2025 置信度 0.80
• Retraction Note: Sentimental analysis based federated learning privacy detection in fake web recommendations using blockchain model.
  europepmc 2026 置信度 0.80
• Sparsity-Aware Edge Caching in IoVs with Asynchronous Federated and Deep Reinforcement Learning
  Abstract The edge content caching technology of the Internet of Vehicles (IoVs) is a key technology to reduce the latency of content access. However, within the hotspot area, with a large number of content access requests generated by vehicle users, the rapid …
  europepmc Jing Gao, Jiahui Chen, Yanqi Huan, Liuyang Wu 2025 置信度 0.80
• Nine Falsifiable Predictions About Artificial Intelligence and Global Health: A Grounded Forecasting Framework from the Global South (2025–2075)
  europepmc 2026 置信度 0.80
• Federated CT foundation models for multi-center detection of lymph node metastasis in pancreatic cancer.
  Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies, with prognosis strongly influenced by the presence of lymph node metastasis (LNM). However, preoperative LNM assessment from computed tomography (CT) is limited by low sensiti…
  pubmed Bhalla P, Gaviria DD, Kupczyk P, Hosseini ASA 等 2026 置信度 0.82
• Federated reinforcement learning with constrained markov decision processes and graph neural networks for fair and grid-constrained coordination of large-scale electric vehicle charging networks.
  The rapid proliferation of electric vehicles (EVs) and their spatially clustered charging behaviors have imposed unprecedented challenges on the stability, efficiency, and fairness of power distribution networks. Coordinating large-scale EV clusters across geo…
  europepmc 2025 置信度 0.80
• DualMask: Federated optimization of privacy-utility-efficiency trilemma via orthogonal gradient perturbation and RL-optimized PSO.
  europepmc 2025 置信度 0.80
• Federated Continual Learning Framework for Robust mmWave Human Activity Recognition Under LOS–NLOS Domain Shifts
  europepmc 2025 置信度 0.80
• Privacy-preserving collaborative battery fault warning for massive electric vehicles by heterogeneous data from charging stations.
  europepmc 2025 置信度 0.80
• FedTLRec: Federated Recommendation with Transformer-based Parameter Aggregation and LoRA Compression
  europepmc 2025 置信度 0.80
• FedSER-XAI: PSO-optimized multi-stream cross-attention transformer with graph features for explainable federated speech emotion recognition.
  europepmc 2025 置信度 0.80
• FedCoSR: Personalized Federated Learning With Contrastive Shareable Representations for Label Heterogeneity in Non-IID Data.
  europepmc 2025 置信度 0.80
• A MARL-federated blockchain-based quantum secure framework for trust management in industrial internet of things.
  europepmc 2025 置信度 0.80
• Cross domain fault diagnosis in internal combustion engines using multisensor data with transfer federated and transformer based federated transfer learning.
  europepmc 2025 置信度 0.80
• Multi agent federated reinforcement learning for Distributed MPTCP Agents
  Abstract The integration of Multi access Edge Computing (MEC) with low Earth orbit (LEO) satellite constellations is a promising paradigm for global, low latency connectivity. However, the dynamic topology and heterogeneous link qualities of satellite networks…
  europepmc Jorge Abraham Rios Suarez, Min Jia, C. Shibwabo Anyembe 2025 置信度 0.80
• Privacy-Preserving Hierarchical Fog Federated Learning (PP-HFFL) for IoT Intrusion Detection.
  europepmc 2025 置信度 0.80
• Quantum Veil Protocol (QVP): A Five-Pillar Post-Quantum Defensive Architecture for AI Governance, Cybersecurity, and Mission-Critical Digital Statecraft
  Quantum Veil Protocol (QVP)™ Foundational Prototype Edition v1.0 A Five-Pillar Post-Quantum Defensive Architecture for AI Governance, Cybersecurity, Digital Sovereignty and Mission-Critical Digital Resilience Authors Bidyut MazumdarIndependent ResearcherORCID:…
  datacite Bidyut, Mazumdar 2025 置信度 0.66
• danielke32/FL_malaria: FederatedMalaria
  Federated Learning for Privacy-Preserving Malaria Prediction Multi-Scenario Evaluation Using Ghana DHS Data Overview This repository contains the complete implementation for the MSc thesis: "Federated Learning for Privacy-Preserving Malaria Prediction: Multi-S…
  datacite Daniel Kwasi Kovor 2026 置信度 0.66
• danielke32/FL_malaria: FederatedMalaria
  Federated Learning for Privacy-Preserving Malaria Prediction Multi-Scenario Evaluation Using Ghana DHS Data Overview This repository contains the complete implementation for the MSc thesis: "Federated Learning for Privacy-Preserving Malaria Prediction: Multi-S…
  datacite Daniel Kwasi Kovor 2026 置信度 0.66
• Federated Learning: A Systematic Review of Architecture, Challenges and Research Directions
  Federated Learning (FL) has emerged as a distributed machine learning paradigm that enables collaborative model training while preserving data privacy. Unlike traditional centralized learning frameworks which require collecting raw data at a single server, FL …
  datacite Rathod, Dr. Nachiket, Pete, Shravani Sushil, Dhoke, Divya Dineshrao, Kurhekar, Ishika Santosh 2026 置信度 0.66 Federated Learning (FL), Distributed Machine Learning, Privacy-Preserving Machine Learning, Horizontal FL, Vertical FL, Federated Transfer Learning, Secure Aggregation, Non-IID Data, Communication Efficiency, Scalability, Adversarial Attacks, Fairness-Aware Aggregation, Blockchain-Based Trust.
• Federated Learning: A Systematic Review of Architecture, Challenges and Research Directions
  Federated Learning (FL) has emerged as a distributed machine learning paradigm that enables collaborative model training while preserving data privacy. Unlike traditional centralized learning frameworks which require collecting raw data at a single server, FL …
  datacite Rathod, Dr. Nachiket, Pete, Shravani Sushil, Dhoke, Divya Dineshrao, Kurhekar, Ishika Santosh 2026 置信度 0.66 Federated Learning (FL), Distributed Machine Learning, Privacy-Preserving Machine Learning, Horizontal FL, Vertical FL, Federated Transfer Learning, Secure Aggregation, Non-IID Data, Communication Efficiency, Scalability, Adversarial Attacks, Fairness-Aware Aggregation, Blockchain-Based Trust.
• Artificial Intelligence and Big Data Integration: A Systematic Literature Review of Technological Trends, Ethical Challenges, and Future Directions
  The convergence of Artificial Intelligence (AI) and Big Data has emerged as a transformative force across industries, yet the literature remains fragmented across technical, ethical, and sectoral domains. This study presents a systematic literature review guid…
  datacite Siregar, Torang 2026 置信度 0.66
• Artificial Intelligence and Big Data Integration: A Systematic Literature Review of Technological Trends, Ethical Challenges, and Future Directions
  The convergence of Artificial Intelligence (AI) and Big Data has emerged as a transformative force across industries, yet the literature remains fragmented across technical, ethical, and sectoral domains. This study presents a systematic literature review guid…
  datacite Siregar, Torang 2026 置信度 0.66
• Correction: Multi-modal dataset creation for federated learning with DICOM-structured reports (International Journal of Computer Assisted Radiology and Surgery, (2025), 20, 3, (485-495), 10.1007/s11548-025-03327-y)
  In the original version of this article, the affiliation details for authors were incorrectly given.
  datacite Tölle, Malte, Burger, Lukas, Kelm, Halvar, André, Florian 等 2026 置信度 0.66
• A Survey on Federated Learning for Privacy-Preserving Artificial Intelligence in Internet of Things Systems
  🔹 Overview The explosive growth of the Internet of Things (IoT) has led to billions of connected devices generating vast amounts of sensitive data. While traditional machine learning relies on centralized data collection, this approach raises significant priv…
  datacite Arjit Sharma 2026 置信度 0.66 Federated LearningInternet of ThingsPrivacy-Preserving Machine LearningEdge ComputingDifferential Privacy
• A Survey on Federated Learning for Privacy-Preserving Artificial Intelligence in Internet of Things Systems
  🔹 Overview The explosive growth of the Internet of Things (IoT) has led to billions of connected devices generating vast amounts of sensitive data. While traditional machine learning relies on centralized data collection, this approach raises significant priv…
  datacite Arjit Sharma 2026 置信度 0.66 Federated LearningInternet of ThingsPrivacy-Preserving Machine LearningEdge ComputingDifferential Privacy
• Beyond the Hype: A Structured Scoping Review of Knowledge Distillation for Accessible and Equitable AI in Education
  Large language models (LLMs) hold substantial potential for educational applications, including automated essay scoring, short-answer grading, personalized feedback, and interactive tutoring, yet their widespread deployment remains constrained by high computat…
  datacite Ahmed, Sarfraz 2026 置信度 0.66 Knowledge distillationEducational AIAutomated essay scoringModel compressionReasoning distillation
• Beyond the Hype: A Structured Scoping Review of Knowledge Distillation for Accessible and Equitable AI in Education
  Large language models (LLMs) hold substantial potential for educational applications, including automated essay scoring, short-answer grading, personalized feedback, and interactive tutoring, yet their widespread deployment remains constrained by high computat…
  datacite Ahmed, Sarfraz 2026 置信度 0.66 Knowledge distillationEducational AIAutomated essay scoringModel compressionReasoning distillation
• The Ring as Machine : A Mixed-Radix, LUT-Mediated, Self-Organizing Computational Architecture : Topological Computation Through Mixed-Radix Phase Lattices
  The Ring as Machine : A Mixed-Radix, LUT-Mediated, Self-Organizing Computational Architecture : Topological Computation Through Mixed-Radix Phase Lattices : 10.5281/zenodo.18188896 Vening, E. J.-P. (2026). The Ring as Machine : A Mixed-Radix, LUT-Mediated, Sel…
  datacite Vening, Edwin Jean-Paul 2026 置信度 0.66
• The Ring as Machine : A Mixed-Radix, LUT-Mediated, Self-Organizing Computational Architecture : Topological Computation Through Mixed-Radix Phase Lattices
  The Ring as Machine : A Mixed-Radix, LUT-Mediated, Self-Organizing Computational Architecture : Topological Computation Through Mixed-Radix Phase Lattices : 10.5281/zenodo.18188896 Vening, E. J.-P. (2026). The Ring as Machine : A Mixed-Radix, LUT-Mediated, Sel…
  datacite Vening, Edwin Jean-Paul 2026 置信度 0.66
• Differentiated Aggregation to Improve Generalization in Federated Learning
  This paper focuses on reducing the communication cost of federated learning by exploring generalization bounds and representation learning. We first characterize a tighter generalization bound for one-round federated learning based on local clients' generaliza…
  datacite Gholami, Peyman, Seferoglu, Hulya 2024 置信度 0.66 Machine Learning (cs.LG)Artificial Intelligence (cs.AI)FOS: Computer and information sciences
• Computational Biology vs Bioinformatics: A 2025 Guide for Biomedical Researchers
  This comprehensive guide for biomedical researchers and drug development professionals delineates the distinct yet complementary roles of bioinformatics and computational biology. Bioinformatics is defined as the field focused on developing and applying comput…
  datacite computational biological science 2026 置信度 0.66 bioinformaticscomputational biologydrug discoverygenomicsmulti-omics
• Computational Biology vs Bioinformatics: A 2025 Guide for Biomedical Researchers
  This comprehensive guide for biomedical researchers and drug development professionals delineates the distinct yet complementary roles of bioinformatics and computational biology. Bioinformatics is defined as the field focused on developing and applying comput…
  datacite computational biological science 2026 置信度 0.66 bioinformaticscomputational biologydrug discoverygenomicsmulti-omics
• Copyright
  crossref 2025-03-07T12:49:06Z 置信度 0.70
• Perspective of Blockchain, Federated Learning, Smart Cities, and Economy
  crossref Rahul Vadisetty 2025-10-03T21:19:49Z 置信度 0.70
• Bibliography
  crossref 2025-03-07T12:49:41Z 置信度 0.70
• FedSemiSelf: A Hybrid Semi-Self-Supervised Federated Learning Framework
  crossref Fotios Filippou, Fotis Foukalas, Theodoros Tsiftsis 2026-01-20T20:38:34Z 置信度 0.70
• HVCFL: Hybrid Centralized-Decentralized Federated Learning for VANETs
  crossref Luiz Fernando Rodrigues da Fonseca, Luiz Fernando Bittencourt 2026-01-20T20:38:34Z 置信度 0.70
• Hybrid-Regularized Magnitude Pruning for Robust Federated Learning Under Covariate Shift
  crossref Özgü Göksu, Nicolas Pugeault 2026-01-20T20:38:34Z 置信度 0.70
• Enhancing MRI reconstruction with cross-silo federated learning
  crossref Pengfei Guo, Puyang Wang, Jinyuan Zhou, Shanshan Jiang 等 2025-03-07T12:49:38Z 置信度 0.70
• Contents
  crossref 2025-03-07T12:49:08Z 置信度 0.70
• A Privacy-Preserving Federated Learning Framework with Multiparty Threshold Homomorphic Encryption
  crossref Svetlana Boudko, Kristian Teig Grønvold 2026-01-20T20:38:34Z 置信度 0.70
• Index
  crossref 2025-03-07T12:49:41Z 置信度 0.70
• Federated Residual Reinforcement Learning for Collaborative Robot Skill Learning in Industry
  crossref Khalil Abuibaid, Vinit Hegiste, Tatjana Legler, Achim Wagner 等 2026-01-20T20:38:34Z 置信度 0.70
• FedLoRASwitch: Efficient Federated Learning via LoRA Expert Hotswapping and Routing
  crossref Joakim Flink, Bostan Khan, Masoud Daneshtalab 2026-01-20T20:38:34Z 置信度 0.70
• Eco-Friendly Federated Learning: Designing a FinOps Framework for Multicloud Resource Coordination
  crossref Francesco Avella, Fabrizio Silvestri 2026-01-20T20:38:34Z 置信度 0.70
• Optimizing Federated Learning by Entropy-Based Client Selection
  crossref Andreas Lutz, Gabriele Steidl, Karsten Müller, Wojciech Samek 2026-01-20T20:38:34Z 置信度 0.70
• A Platform to Integrate Data Governance in Federated Learning
  crossref José Antonio Peregrina, Guadalupe Ortiz, Christian Zirpins 2026-01-20T20:38:34Z 置信度 0.70
• Federated Cyber Intelligence
  crossref Hamed Tabrizchi, Ali Aghasi 2025-04-23T18:07:47Z 置信度 0.70
• Front Matter
  crossref 2025-03-07T12:49:07Z 置信度 0.70
• DNA BASED FEDERATED LEARNING
  The Deoxyribonucleic Acid (DNA) can be considered as one of the most effective biometrics. It can be used in different fields such as personal identification, parental verification and relativity. In this study, federated learning is suggested. It is a type of…
  crossref Raid Al-Nima, Maan Yahya, Azzah Qaba 2026-05-20T10:23:13Z 置信度 0.70
• Analyzing the Impact of Participant Failures in Cross-Silo Federated Learning
  crossref Fabian Stricker, David Bermbach, Christian Zirpins 2026-01-20T20:38:34Z 置信度 0.70
• Optimizing Federated Learning with Frequency-Domain Quantization and Network-Aware Adaptive Compression
  crossref Syeda Faiza Ahmed, Lafifa Jamal 2026-01-20T20:38:34Z 置信度 0.70
• Enhancing the Convergence of Federated Learning Aggregation Strategies with Limited Data
  crossref Judith Sáinz-Pardo Díaz, Álvaro López García 2026-01-20T20:38:34Z 置信度 0.70
• Federated Learning Architecture for Self-Improving Biometric Access Control in Office Buildings
  crossref Dennis Grüneberg, Lennart Schiweck, Christian Kücherer 2026-01-20T20:38:34Z 置信度 0.70
• Intelligent recognition system based on federated learning
  crossref 2025-04-13T02:44:42Z 置信度 0.70
• 2025 3rd International Conference on Federated Learning Technologies and Applications (FLTA)
  crossref 2026-01-20T20:39:20Z 置信度 0.70
• Impact of Client-Side Update Strategies on Gradient Inversion Leakage in Federated Learning
  crossref Safaá Fallatah, Alexei Lisitsa, Floriana Grasso 2026-01-20T20:38:34Z 置信度 0.70
• Federated Learning: Collaborative Machine Learning Without Data Sharing
  crossref 2025-12-04T08:01:59Z 置信度 0.70
• Towards Lightweight Input Control for Cross-Device Federated Learning With Dynamic Participation
  crossref Christoph Düsing, Philipp Cimiano 2025-12-02T17:01:43Z 置信度 0.70
• Detect, Adapt, Overcome: Mitigating Concept Drift in Federated Learning
  crossref Iftekhar Rahman, Nisal Hemadasa, Dominik Kaaser, Pierre-Alexandre Murena 等 2026-01-20T20:38:34Z 置信度 0.70
• Trans-XFed: An Explainable Federated Learning for Supply Chain Credit Assessment
  crossref Jie Shi, Arno P. J. M. Siebes, Siamak Mehrkanoon 2026-01-20T20:38:34Z 置信度 0.70
• Closing Thoughts, and Future Directions in Federated Cyber Intelligence
  crossref Hamed Tabrizchi, Ali Aghasi 2025-04-23T18:07:47Z 置信度 0.70
• Comparison of Convergence Rates in Federated Learning and Federated Multi-Task Learning Using the CIFAR-10 Dataset
  crossref Truptee Upadhye, Preethi Nanjundan 2025-03-24T17:54:32Z 置信度 0.70
• Integrating Multimodal Fitness Data Through Federated Learning Frameworks
  This review synthesizes published methods for integrating multimodal fitness data-physiological (heart rate, HRV, SpO 2 , skin temperature), kinematic (accelerometer, gyroscope, cadence, stride), textual self-reports (RPE, fatigue, sleep, diet), and structured…
  crossref Jackson Duane 2025-10-24T02:41:45Z 置信度 0.70
• Federated Learning in the Healthcare Industry
  crossref Ramkrishna Mondal 2025-09-26T06:00:16Z 置信度 0.70
• Federated Multi-Modal Learning for Manufacturing: A Privacy-Preserving Approach to Distributed Sensor Fusion
  crossref Tatjana Legler, Vinit Hegiste, Martin Ruskowski 2026-01-20T20:38:34Z 置信度 0.70
• Federated Learning Applications In Enterprise Network Management
  The fast expansion of connected devices and the need for improved security and performance provide growing challenges for enterprise network administration. Because of scalability and privacy issues, traditional centralized network management techniques freque…
  crossref Ravikumar Perumallaplli 2025-05-06T16:05:37Z 置信度 0.70