Research trend analysis of abnormal behavior detection based on knowledge networks

Shilong Wang; Maylor Karhang Leung; Siak Wang Khor

doi:10.1117/12.3029296

16 May 2024 Research trend analysis of abnormal behavior detection based on knowledge networks

Shilong Wang, Maylor Karhang Leung, Siak Wang Khor

Proceedings Volume 13166, International Conference on Remote Sensing Technology and Survey Mapping (RSTSM 2024); 131660X (2024) https://doi.org/10.1117/12.3029296
Event: International Conference on Remote Sensing Technology and Survey Mapping (RSTSM 2024), 2024, Changchun, China

Abstract

This research employs CiteSpace software to analyze research outcomes on Abnormal Behavior Detection Based on Video Surveillance. It focuses on the China National Knowledge Infrastructure Database (CNKI) and the "Web of Science" Database, aiming to identify research trends, provide some references for advancing this research direction. The following conclusions are drawn: (1) The literature on abnormal behavior detection models and algorithms has shown a consistent increase over time. (2) The current research trend is deep learning, video surveillance and abnormal detection. Research tends to diversify. (3) In China and abroad, there is more attention in the field of deep learning, video surveillance and anomaly detection.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Shilong Wang, Maylor Karhang Leung, and Siak Wang Khor "Research trend analysis of abnormal behavior detection based on knowledge networks", Proc. SPIE 13166, International Conference on Remote Sensing Technology and Survey Mapping (RSTSM 2024), 131660X (16 May 2024); https://doi.org/10.1117/12.3029296

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