Anomaly Detection Techniques and Applications
This cluster of papers focuses on the detection of anomalies in high-dimensional data, particularly in the context of video analysis, surveillance, and time series data. It covers a wide range of techniques including unsupervised learning, outlier detection, deep learning, and novelty detection for identifying abnormal patterns and events.
Papers listed on taxonomy pages are the top few works per node from the OpenAlex snapshot. That list is not exhaustive and is not an endorsement. The topic map and the journal registry remain separate: there is still no authoritative topic-to-venue or topic-to-organization edge. Search is a lexical lookup, not a claim that a venue publishes a topic.