federated learning

An Adaptive and Interpretable Federated Deep Learning Architecture for Privacy-Aware Network Threat Classification

The increasing distribution of enterprise computing across cloud platforms, edge devices, branch networks, and Internet-of-Things environments has made the collection and centralized analysis of network telemetry increasingly difficult. Conventional deep-learning intrusion detection approaches commonly require the move...

An adaptive federated few-shot learning method with intelligent device selection

Federated learning, which enables the training of intelligent models without transferring data and solely by relying on the computational capabilities of distributed devices, faces significant challenges in few-shot scenarios due to data heterogeneity, resource constraints, and slow convergence. The primary obstacle li...

EduSense - A Real-Time IoT-Augmented Explainable Ensemble Learning Framework With Face-Verified Attendance For Early Academic Risk Detection In Engineering Education

Engineering colleges across India face a critical challenge, with approximately 28% of enrolled students failing to complete their degrees on time. In regions like Vidarbha, Maharashtra, this rate is exacerbated by localized financial stress, first-generation academic backgrounds, and constrained support systems. Tradi...

Artificial Intelligence-Driven Theranostics: Integrating Machine Learning For Precision Diagnosis And Personalized Therapy

Theranostics links disease characterization with treatment selection and response assessment, creating a framework in which diagnostic information directly informs individualized therapy. Recent advances in artificial intelligence (AI), machine learning (ML), deep learning, radiomics, radiogenomics, and multimodal data...

An Adaptive and Interpretable Federated Deep Learning Architecture for Privacy-Aware Network Threat Classification

The increasing distribution of enterprise computing across cloud platforms, edge devices, branch networks, and Internet-of-Things environments has made the collection and centralized analysis of network telemetry increasingly difficult. Conventional deep-learning intrusion detection approaches commonly require the move...

song1741008932-ship-it/FedDWM: v1.2

FedDWM: A Dynamic Watermark Migration Framework for Model Poisoning Defense in Federated Learning

The Role of Smart Systems and Machine Learning in Business Decision-Making: A Bibliometric Review

The Changing Landscape of Plant Disease Detection: The Role of Artificial Intelligence

Plant diseases constrain agricultural productivity and food security, while conventional diagnosis depends heavily on visible symptoms and specialist expertise, limiting rapid and scalable assessment across heterogeneous agricultural environments. Artificial intelligence (AI), particularly machine learning, deep learni...

Quantum-Enhanced Federated Learning Framework for Next-Generation AIoT Systems: Bridging Neuromorphic Computing and Environmental Intelligence

song1741008932-ship-it/FedDWM: v1.2

FedDWM: A Dynamic Watermark Migration Framework for Model Poisoning Defense in Federated Learning

Securing the open-source ecosystem: AI-enhanced and explainable supply chain security for reliable software development

Modern software supply chains face increasing risks from vulnerable and anomalous dependencies, necessitating automated and interpretable detection methods integrated within Continuous Integration and Continuous Deployment (CI/CD) workflows. Open-source software (OSS) ecosystems are increasingly targeted by sophist...

Cadre Stratégique pour l'Infrastructures Immobilière Éco-Résilience : Déclaration d'Antériorité Complète et Divulgation Habilitante

Résumé FRCe document, produit avec l’assistance de Gemini 3 Raisonnement, est publié sous licence Apache 2.0. Il constitue une publication défensive volontaire (antériorité) et entre de ce fait dans l’état de la technique au sens des législations applicables : art. L 611-11 CPI (Code de la propriété intellectuelle fran...