AADC-Net: A Multimodal Deep Learning Framework for Automatic Anomaly Detection in Real-Time Surveillance

Duc Tri Phan; Vu Hoang Minh Doan; Jaeyeop Choi; Byeong-Il Lee; Junghwan Oh

doi:10.1109/tim.2025.3551832

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AADC-Net: A Multimodal Deep Learning Framework for Automatic Anomaly Detection in Real-Time Surveillance

Duc Tri Phan Vu Hoang Minh Doan Jaeyeop Choi Byeong-Il Lee Junghwan Oh

Year: 2025 Journal: IEEE Transactions on Instrumentation and Measurement Vol: 74 Pages: 1-13 Publisher: Institute of Electrical and Electronics Engineers

DOI: 10.1109/tim.2025.3551832

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Keywords:

Anomaly detection Computer science Artificial intelligence Object detection Deep learning Computer vision Real-time computing Pattern recognition (psychology)

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9.64

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0.96

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Citation History

Topics

Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Network Security and Intrusion Detection

Physical Sciences → Computer Science → Computer Networks and Communications

Advanced Malware Detection Techniques

Physical Sciences → Computer Science → Signal Processing

AADC-Net: A Multimodal Deep Learning Framework for Automatic Anomaly Detection in Real-Time Surveillance

Metrics

Citation History

Topics

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