Unlike pattern-matching, which is about spotting connections and relationships, when we detect anomalies we are seeing disconnections—things that do not fit together. Anomalies get much less attention ...

Hyperspectral anomaly detection techniques represent a rapidly evolving area in remote sensing, combining advanced machine learning with signal processing to identify outlying elements in ...

Internet of Things (IoT) devices have become extremely popular in homes and workplaces. However, their abundant and rising usage also makes these products tempting targets for cybercriminals. Anomaly ...

Anomaly detection is one of the more difficult and underserved operational areas in the asset-servicing sector of financial institutions. Broadly speaking, a true anomaly is one that deviates from the ...

Dr. James McCaffrey from Microsoft Research presents a complete program that uses the Python language LightGBM system to create a custom autoencoder for data anomaly detection. You can easily adapt ...

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, ...