Provide practical KPIs to monitor, including FA hit rate (percent of FAs that find root cause) and time to address yield ...
That challenge is examined in the study Towards Eco-Friendly Cybersecurity: Machine Learning-Based Anomaly Detection with ...
Abstract: Guided wave-based structural health monitoring is extensively utilized in various industrial applications to ensure the integrity of components within industrial systems. Among these ...
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, ...
Researchers at Google’s Threat Intelligence Group (GTIG) have discovered that hackers are creating malware that can harness the power of large language models (LLMs) to rewrite itself on the fly. An ...
Cloud infrastructure anomalies cause significant downtime and financial losses (estimated at $2.5 M/hour for major services). Traditional anomaly detection methods fail to capture complex dependencies ...
College of Robotics, Guangdong Polytechnic of Science and Technology, Zhuhai, Guangdong, China To address the issues of low detection accuracy and poor real-time performance in existing methods for ...
Department of Electronics Communication Engineering, SRM Institute of Science and Technology, Vadapalani Campus, Chennai, India Introduction: Early and accurate detection of crop stress is vital for ...
Fully 87% of game developers are already using AI agents. That's according to a new survey from Google Cloud and The Harris Poll of 615 game developers in the United States, South Korea, Norway, ...