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 ...
Visual Studio Magazine

Data Anomaly Detection Using a Neural Autoencoder with C#

Data anomaly detection is 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. There are many different types of ...
EurekAlert!

Chung-Ang University researchers review deep learning-based methods to detect time series data anomaly

Researchers analyze state-of-the-art approaches, limitations, and applications of deep learning-based anomaly detection in multivariate time series Monitoring financial security, industrial safety, ...
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, ...
Devdiscourse

Self-supervised AI can unlock hidden disease patterns

Published as an arXiv preprint, the paper details how unsupervised and self-supervised AI models are matching or surpassing supervised systems while uncovering biological patterns that traditional ...
Forbes

US Army Analytics Group – Cybersecurity Anomaly Detection 1000X Faster With Less False Positives

The US Army Analytics Group (AAG) provides analytical services for various organizational operations and functions, including cybersecurity. AAG signed a Cooperative Research and Development Agreement ...
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 ...