STemGAN: spatio-temporal generative adversarial network for video anomaly detection

Automatic detection and interpretation of abnormal events have become crucial tasks in large-scale video surveillance systems. The challenges arise from the lack of a clear definition of abnormality, which restricts the usage of supervised methods. To this end, we propose a novel unsupervised anomal...

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Veröffentlicht in:	Applied intelligence (Dordrecht, Netherlands) Netherlands), 2023-12, Vol.53 (23), p.28133-28152
Hauptverfasser:	Singh, Rituraj, Saini, Krishanu, Sethi, Anikeit, Tiwari, Aruna, Saurav, Sumeet, Singh, Sanjay
Format:	Artikel
Sprache:	eng
Schlagworte:	Anomalies Artificial Intelligence Computer Science Datasets Deep learning Entrances Generative adversarial networks Human error Machines Manufacturing Mechanical Engineering Methods Processes Surveillance Surveillance systems
Online-Zugang:	Volltext
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