Human Trespassing Detection System through Deep Learning
Year: 2025
Type: article
Abstract: Using CCTV footage allows for real-time danger monitoring. In order to deter criminal activity, videosurveillance is used to keep an eye out for suspicious conduct. Nowadays, most store owners have CCTVcameras to catch these suspicious activities, but these systems can't tell when someone is trespassing. Thelack of a faster and more effective method to detect theft would make the task difficult. At this time, themarket offers systems that include trip wires, sensors, and CCTV. This proposal details methods fordetecting and catching shoplifters in confined spaces. In this proposal, we want to transform passivemonitoring into active surveillance by utilizing AI and deep learning approaches. We will assess photos,identify unwanted things, and alert them using neural networks.
Author: Mr.Ashraf Ali Shaikh, Jagtap Nandini, Gatkal Pranali, Kathale Apurva, Rode Amruta
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6968030555
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