Please use this identifier to cite or link to this item: https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/16466
Title: Motion Detection Using Heuristic Ai Based Machine Learning Approaches
Authors: Rajesh Sharma, R
Rajiv Gandhi, K
Shanmugaraja, K
Sungheetha, Akey
Chinnaiyan, R
Jegan, J
Keywords: And Suspicious Activity Detection
Convolutional Neural Networks
Deep Learning
Issue Date: 2024
Publisher: 4th International Conference on Innovative Practices in Technology and Management 2024, ICIPTM 2024
Institute of Electrical and Electronics Engineers Inc.
Citation: pp. 1-4
Abstract: Due to the rise in shootings, knife assaults, terrorist attacks, etc. that occur in public spaces around the world, it has become crucial to identify suspicious activity in these areas. This study employs convolutional neural networks and deep learning to identify suspicious activity in videos and photos. We examine various CNN architectures and contrast their precision. We describe the design of our system, which can analyze live video feed from cameras and determine whether an activity is suspicious or not. We also make suggestions for potential future advancements in the field of detecting suspicious activity. © 2024 IEEE.
URI: https://doi.org/10.1109/ICIPTM59628.2024.10563768
https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/16466
ISBN: 9798350307757
Appears in Collections:Conference Papers

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