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federated learning

2,055 papers

#federated learning Open access Sep 2026

The Dual Use of Generative Artificial Intelligence in Cybersecurity: A Survey from Deepfake Attacks to Intelligent Defense

The rapid iteration of generative Artificial Intelligence (AI) is reshaping the cybersecurity offense-defense landscape. This paper systematically reviews research progress in this field from 2021 to 2026, focusing on the dual use of generative AI in cybersecurity. On the one hand, malicious actors exploit generative A...

Dalin Xiang, Xinkai Fu · 0 citations
#federated learning Open access Sep 2026

IoT-Based Elderly Health Monitoring Information System with Federated Learning for Early Health Risk Prediction

The growing elderly population in Indonesia is directly associated with an increasing burden of non- communicable diseases such as hypertension, heart disease, diabetes mellitus, and chronic obstructive pulmonary disease (COPD), creating a need for continuous rather than periodic health-monitoring mechanisms. This stud...

Ilham Satya Nugraha, Erwin Halim · 0 citations

An Edge Intelligence Method for Learning-State Recognition and Personalized Feedback in Higher Education

To address fluctuations in multimodal data quality, client heterogeneity, and insufficient feedback timeliness in university classrooms, this paper proposes a cloud-edge-device collaborative method, HE-EdgePF. The method integrates visual, audio, textual, and platform-behavior features through quality-aware dynamic gat...

Jing-Xuan Fang, Hong Chen · 0 citations
#federated learning Book Sep 2026

Federated Edge Intelligence for Real-Time Obstacle Detection in Vehicular Networks

Obstacle detection is the perception task where delay is measured against the laws of motion, and cloud centred inference cannot meet that budget without also spending bandwidth and exposing sensor data. This chapter develops Federated Edge Intelligence, a three tier design uniting Federated Learning with Multi-Access...

Meghna B. Patel, Patel Devarshi, Neha Mewani et al. · 0 citations
#federated learning Book Sep 2026

Emerging Edge Intelligence and Next-Generation Communication Technologies for Secure and Sustainable Intelligent Transportation Systems

The advancement of AI, IoT, 6G, and UAV technologies is enabling Intelligent Transportation Systems (ITS) to evolve into connected and autonomous mobility ecosystems. This chapter proposes an integrated framework for developing ITS and discusses how EdgeAI enables low-latency and privacy-aware decision-making by integr...

Neetu Sharma, Manoj Shahu, Kamlesh Vaishnav · 0 citations
#federated learning Open access Sep 2026

Enhancing Precision Weed Management with Federated Learning-Based GAN and Transfer Learning

Precision weed management is critical to sustainable cotton production because overuse of herbicides can have detrimental environmental and health effects and increase production costs. The problem of weed recognition from field images is still difficult even with complex background, intra-class variation, class imbala...

Ankur Kulhari, Sanjeev Patwa · 0 citations
#federated learning Review Open access Sep 2026

COMPARATIVE ANALYSIS OF FOG SYSTEM ARCHITECTURE OPTIMIZATION METHODS: FROM METAHEURISTICS TO HYBRID SOLUTIONS

The rapid proliferation of Internet of Things devices has intensified demands on distributed computing infrastructures, making fog computing — a paradigm that positions computational resources at the network edge — a critical enabler of low-latency real-time applications. Optimally placing services across fog nodes is...

Oleksandr Sbitnev, Lyudmila Voloshchuk · 0 citations
#federated learning Review Open access Sep 2026

A Comprehensive Review on Federated and Incremental Learning in Spatial Crowdsourcing Systems

Spatial Crowdsourcing (SC) coordinates workers and requesters through personal mobile devices to complete location‐dependent tasks in real time. The combination of continuous worker mobility, self‐interested participants, and real‐time service requirements creates a learning environment that is more adversarial, more...

Md. Mujibur Rahman, Q. Mamun, Michael Bewong et al. · 0 citations
#federated learning Book Sep 2026

Edge AI-Driven Traffic Management for Urban Air Mobility

Cloud-centric Air Traffic Management architectures are poorly suited to Urban Air Mobility, where dense, three-dimensional flight paths require conflict-resolution decisions within tens of milliseconds. This chapter proposes a four-layer, edge-native reference architecture combining Deep Reinforcement Learning for adap...

Nitesh Kumar, Vikash Kumar · 0 citations
#federated learning Open access Sep 2026

Digital Challenges to the Protection of Personal Data

This report argues that the challenges facing the protection of personal data in the digital age are complex and interwoven, arising from the interaction between rapid technical development, notably artificial intelligence and big data, and legislative deficiency. It adopts a descriptive-analytical and comparative meth...

Abderrahmane Belouafi Ben Haiba · 0 citations
#federated learning Open access Sep 2026

Federated Explainable Multi-Agent Governance Framework for Adaptive Personalized Learning Equity in Higher Education

The rapid deployment of artificial intelligence (AI) in higher education raises questions of equity, transparency, accountability, privacy, and governance in adaptive personalized learning. While AI-enabled personalization can increase educational responsiveness, top-down personalized learning architectures may reinfor...

Kamal Singh Kunwar · 0 citations

From tech blogs

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MIT News · Artificial Intelligence Oct 23, 2026

Q&A: How AI came to model the “messy” human mind

Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.

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