Researchers from Politecnico di Milano propose a data-driven water leak detection method that treats leaks as anomalies in ...
Discover how AI-driven anomaly detection safeguards post-quantum context streams in Model Context Protocol (MCP) environments, ensuring robust security for AI infrastructure against future threats.
Dr. James McCaffrey presents a complete end-to-end demonstration of anomaly detection using k-means data clustering, implemented with JavaScript. Compared to other anomaly detection techniques, ...
Explore behavioral analysis techniques for securing AI models against post-quantum threats. Learn how to identify anomalies and protect your AI infrastructure with quantum-resistant cryptography.
Researchers in Slovakia have demonstrated a machine-learning framework that predicts PV inverter output and detects anomalies using only electrical and temporal data, achieving 100% accuracy in ...
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US researchers say a self-supervised machine-learning tool can identify long-term physical defects in solar assets weeks or years before conventional inspections, potentially reducing operations and ...
The software tool developed by Stony Brook University uses self-supervised learning to detect long-term solar equipment damage weeks or years before manual inspections find it.
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