Enhanced Anomaly Detection in Pandemic Surveillance Videos: An Attention Approach With EfficientNet-B0 and CBAM Integration

Enhanced Anomaly Detection in Pandemic Surveillance Videos: An Attention Approach With EfficientNet-B0 and CBAM Integration

We present a novel system for anomaly detection in surveillance videos, specifically focusing on identifying instances where individuals deviate from public health guidelines during the pandemic. These anomalies encompassed behaviours like the absence of face masks, incorrect mask usage, coughing, n...

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Bibliographic Details
Main Authors: Sareer Ul Amin, Muhammad Sibtain Abbas, Bumsoo Kim, Yonghoon Jung, Sanghyun Seo
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Anomaly detection
video surveillance
computer vision
attention method
intelligent surveillance system
Online Access:https://ieeexplore.ieee.org/document/10740272/
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https://ieeexplore.ieee.org/document/10740272/

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