Object-centric and memory-guided network-based normality modeling for video anomaly detection

S. Chandrakala; P Shalmiya; V. Srinivas; K. Deepak

doi:10.1007/s11760-022-02161-y

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Object-centric and memory-guided network-based normality modeling for video anomaly detection

S. Chandrakala P Shalmiya V. Srinivas K. Deepak

Year: 2022 Journal: Signal Image and Video Processing Vol: 16 (7)Pages: 2001-2007 Publisher: Springer Science+Business Media

DOI: 10.1007/s11760-022-02161-y

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Keywords:

Autoencoder Anomaly detection Computer science Benchmark (surveying) Artificial intelligence Normality Residual Generalization Anomaly (physics) Pattern recognition (psychology) Object (grammar) Object detection Task (project management) Machine learning Computer vision Deep learning Algorithm

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Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Network Security and Intrusion Detection

Physical Sciences → Computer Science → Computer Networks and Communications

Artificial Immune Systems Applications

Physical Sciences → Engineering → Biomedical Engineering

Object-centric and memory-guided network-based normality modeling for video anomaly detection

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