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Exploring Deep Learning Paradigms: A Comprehensive Analysis of Object Detection Methods for Suspicious Activities in Video Surveillance

Anju K.P, Dr. Sunitha C

Abstract


The advent of Deep Learning has introduced a new dimension to image/video processing and computer vision applications. Object detection, a key application of deep learning, distinguishes itself through feature learning and representation compared to traditional methods. Video surveillance plays a crucial role in security by identifying suspicious activities, making their detection a primary focus in surveillance videos. Numerous deep learning-based object detection algorithms exist for this purpose. This paper explores various object detection methods employed in detecting suspicious activities, discussing their re-spective strengths and weaknesses.


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References


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