Semiconductor Engineering

Why Scan Diagnosis Should Be Part Of Every Fabless Company’s Yield Playbook

Provide practical KPIs to monitor, including FA hit rate (percent of FAs that find root cause) and time to address yield ...
The Aviationist

U.S. Navy Continues BQM-177 Target Drone Demos with Hivemind AI

The U.S. Navy demonstrated the manned-unmanned teaming capabilities of BQM-177s using Shield AI’s Hivemind software in a simulated CCA air combat ...
Devdiscourse

Energy-hungry cybersecurity models put climate goals at risk

That challenge is examined in the study Towards Eco-Friendly Cybersecurity: Machine Learning-Based Anomaly Detection with ...
IEEE

Improved PCA Reconstruction-Based Unsupervised Anomaly Detection in Uncontrolled Structural Health Monitoring With Correntropy

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 ...
Visual Studio Magazine

Anomaly Detection Using K-Means Clustering with JavaScript

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, ...
Futurism

Malware Is Now Using AI to Rewrite Its Own Code to Avoid Detection

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 ...
Scientific Research Publishing

Graph Neural Networks for Anomaly Detection in Cloud Infrastructure ()

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 ...
Frontiers

Design of a real-time abnormal detection system for rotating machinery based on YOLOv8

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 ...
Frontiers

MLVI-CNN: a hyperspectral stress detection framework using machine learning-optimized indices and deep learning for precision agriculture

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 ...