Now showing items 1-1 of 1

    • GridHTM: Grid-Based Hierarchical Temporal Memory for Anomaly Detection in Videos 

      Monakhov, Vladimir; Thambawita, Vajira L B; Halvorsen, Pål; Riegler, Michael (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-02-13)
      The interest in video anomaly detection systems that can detect different types of anomalies, such as violent behaviours in surveillance videos, has gained traction in recent years. The current approaches employ deep learning to perform anomaly detection in videos, but this approach has multiple problems. For example, deep learning in general has issues with noise, concept drift, explainability, ...