This dataset provides reproducibility resources for evaluating federated learning-based maize leaf disease classification under client heterogeneity and cross-domain variation. It supports experiments using an EfficientNet-B0 model trained centrally and through Federated Averaging (FedAvg) with different client data pa...
Abstract Human Digital Twins (HDTs) are an innovative concept in the field of personalized medicine, relying on real-time models of a human body formed via collection and analysis of physiological, clinical, behavioural, and environmental data. Research on HDTs gives evidence to a considerable promise in terms of disea...
The rapid digitalisation of cities in Saudi Arabia is leading to a greater number of connected cameras, access-control devices, environmental sensors, edge gateways and city platforms being used for the protection of people, buildings and critical infrastructure. While these systems can enhance situational awareness, t...
Abdulrahman Alshaikhali· Iconic Research and Engineer...· 0 citations
Unmanned Aerial Vehicles (UAVs) are deployed in mission-critical applications such as surveillance, disaster relief, and ecological monitoring. These use cases demand real-time intelligence from sensitive data, necessitating privacy-preserving distributed learning approaches like Federated Learning (FL). However, conve...
Sophia S., Getzi Jeba Leelipushpam P.· Journal of Trends in Compute...· 0 citations
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The correct and prompt detection of leaf diseases in paddy crops remains essential for protecting agricultural output and yield stability and reducing major losses that occur during severe disease outbreaks. The widespread use of conventional centralized machine learning techniques becomes impractical for real-world ag...
B Johnson, Chandrakumar Thangavel· Tarım Bilimleri Dergisi· 0 citations
Digital transformation has dissolved the boundaries on which conventional network security was built. Cloud platforms, remote work, mobile endpoints, and the Internet of Things have turned organizational networks into distributed, hyper-connected ecosystems in which the perimeter-based “castle-and-moat” model can no lo...
Ahmet Ertuğrul, Kadir Süzme· Özgür Yayınları eBooks· 0 citations
The rapid adoption of artificial intelligence (AI), machine learning (ML), biometric recognition, intelligent transportation systems, distributed energy platforms, and connected vehicles has resulted in increasingly heterogeneous digital infrastructures. Although these systems generate substantial quantities of data an...
Muhammad Qasim, Laraib Tabish, Falak Ali· Zenodo (CERN European Organi...· 0 citations
Saudi digital service platforms are now becoming more reliant on connected devices, the streaming of telemetry data, and automated service orchestration, but the shift from simply observing events to being able to anticipate operational outcomes is still very uneven. This review looks at how Internet of Things (IoT)-ba...
Ahmed Helmi· Iconic Research and Engineer...· 0 citations
This framework combines longitudinal delta-radiomics, wearable biomechanics, and federated learning with calibrated uncertainty for CAI prediction. Treatment-response stratification is hypothesis-generating and needs prospective multicenter validation before clinical use.
EL-RAKHAWI DOCTRINE OF HYPERCOMPUTING AND CONVERGENT AI: SUMMARY This comprehensive technical monograph presents the El-Rakhawi Doctrine of Hypercomputing and Convergent Artificial Intelligence, a world-class blueprint for designing and deploying exascale AI Factories optimized for large language model training and mas...
mohamed kamal arafa el-rakhawi· Zenodo (CERN European Organi...· 0 citations
Biometric signal processing has become essential for authentication and identification in modern security systems, with applications in border control, healthcare, financial services, mobile devices, and the Internet of Things. Although biometric traits such as fingerprints, iris patterns, facial features, voice charac...
I. N Davies· INTERNATIONAL JOURNAL OF COM...· 0 citations
Chemical manufacturers and distributors are increasingly dependent upon a steady stream of data from sensors, lab systems, logistics platforms and connected assets. However, when records are fragmented, unverifiable, or difficult to exchange across organisational boundaries, lifecycle decisions remain exposed to avoida...
Learn how Google DeepMind and GovTech Singapore uses lightweight on-device Gemma models to intercept conversational scams in private chats with zero cloud data egress.
MIT News · Artificial Intelligence· news.mit.eduOct 13, 2026
Machine-learning networks can learn without detailed instructions from a designer. Those that do may offer insight into how the brain reorganizes itself during learning.
Microsoft Research Blog· microsoft.comOct 12, 2026
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 7, 2026
Students in MIT’s Concourse program delve deeply into the human condition, debate challenging questions, and learn to develop judgment about issues that can’t be quantified.
Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them. The post Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses appeared first on Microsoft Research.
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