The software tool uses self-supervised learning to detect long-term defects in solar assets weeks or years before ...

Abstract: The current fast proliferation of the Internet of Things (IoT) networks has made anomaly detection and security more difficult. Traditional methods are not able to detect hostile activities ...

Explore strategies for managing combinatorial explosion in high dimensional anomaly detection to enhance data observability ...

Srinubabu Kilaru said Bringing version control and CI/CD into data pipelines changed how quickly we could respond to policy ...

Discover the best Application Performance Monitoring (APM) tools that enable enterprises to enhance application performance, ensure seamless digital experiences, and drive long-term growth in 2025.

Overview: In 2025, Java is expected to be a solid AI and machine-learning language.Best Java libraries for AI in 2025 can ease building neural networks, predict ...

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 ...

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 ...

From SOCs to smart cameras, AI-driven systems are transforming security from a reactive to a predictive approach. This ...

Researchers from Politecnico di Milano propose a data-driven water leak detection method that treats leaks as anomalies in ...

Abstract: This paper presents a vibration-based machine learning approach for road surface monitoring using smartphone sensors. With Mexico’s road network experiencing significant deterioration and ...