A Dynamic Convolutional Generative Adversarial Network for Video Anomaly Detection

Wěi Zhāng; Ping He; Shengrui Wang; Lizhi An; Fan Yang

doi:10.1007/s13369-022-07096-7

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A Dynamic Convolutional Generative Adversarial Network for Video Anomaly Detection

Wěi Zhāng Ping He Shengrui Wang Lizhi An Fan Yang

Year: 2022 Journal: Arabian Journal for Science and Engineering Vol: 48 (2)Pages: 2075-2085 Publisher: Springer Science+Business Media

DOI: 10.1007/s13369-022-07096-7

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Keywords:

Computer science Anomaly detection Convolutional neural network Artificial intelligence Benchmark (surveying) Robustness (evolution) Pattern recognition (psychology) Recurrent neural network Machine learning Artificial neural network

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Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Artificial Immune Systems Applications

Physical Sciences → Engineering → Biomedical Engineering

Network Security and Intrusion Detection

Physical Sciences → Computer Science → Computer Networks and Communications

A Dynamic Convolutional Generative Adversarial Network for Video Anomaly Detection

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