JSTOR Daily

A Comparison of Multivariate Outlier Detection Methods For Finding Hyperspectral Anomalies

Timothy E. Smetek, Kenneth W. Bauer Jr. Hyperspectral anomaly detection is a useful means for using hyperspectral imagery to locate unusual objects. Current anomaly detection methods commonly use ...
Harvard Business School

Multivariate Unsupervised Machine Learning for Anomaly Detection in Enterprise Applications

Elsner, Daniel, Pouya Aleatrati Khosroshahi, Alan MacCormack, and Robert Lagerström. "Multivariate Unsupervised Machine Learning for Anomaly Detection in Enterprise Applications." Proceedings of the ...
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, ...
SiliconANGLE

Acceldata can now spot data anomalies across multiple dimensions

Data observability vendor Acceldata Inc. today announced Adaptive AI Anomaly Detection capabilities in its xLake Reasoning Engine that automatically identify hidden, multidimensional data anomalies ...