Nature

System log anomaly detection based on contrastive learning and retrieval augmented

System logs are run-time significant events of computer systems recorded by software. By analyzing the system logs, a lot of important information and issues can be detected promptly. Log anomaly ...
Nature

Physics-guided contrastive temporal graph learning for anomaly detection and root-cause localization in industrial control systems

Industrial Control Systems (ICS) are becoming more important than ever because most of the essential services we use in our daily life depends on them, such as electricity supply, clean water ...
Visual Studio Magazine

Data Anomaly Detection Using a Neural Autoencoder with C#

Dr. James McCaffrey of Microsoft Research tackles the process of examining a set of source data to find data items that are different in some way from the majority of the source items. Data anomaly ...
EurekAlert!

COVAD: Content-oriented video anomaly detection using a self attention-based deep learning model

Video anomaly detection is a research hotspot in the field of computer vision, attracting many researchers.Video anomaly detection differs from traditional video analysis. Usually, abnormal events ...
Electronic Design

Explainable AI for Anomaly Detection

What is explainable AI (XAI)? What are some of the use cases for XAI? What are the technology requirements for implementing XAI? Anomaly detection is the process of identifying when something deviates ...
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, ...