Video Surveillance Anomaly Detection: A Review on Deep Learning Benchmarks

Video Surveillance Anomaly Detection: A Review on Deep Learning Benchmarks

Many surveillance cameras are mounted in sparse and crowded indoor and outdoor areas to monitor and detect various patterns of human behaviors and anomalies in the public and private sectors. The continuous streams from these cameras produce an enormous amount of graphical data. This data featuring...

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Bibliographic Details
Main Authors: Kashaf U. Duja, Izhar Ahmed Khan, Mohammed Alsuhaibani
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Deep learning
convolution neural network (CNN)
video surveillance anomaly detection (VSAD)
state-of-the-art (SOTA) approaches
learning models
datasets
Online Access:https://ieeexplore.ieee.org/document/10744017/
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