Volume 20 No 20 (2022)
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REAL TIME SURVEILLANCE USING DEEPLEARNING
Mr. DHANUSH MUNAGALA , Miss. A NARMADA
Abstract
Basic capabilities like video recording and archiving are all that traditional video surveillance offers. It cannot distinguish between approved and unauthorised faces. A vital component of contemporary cities' security and defence systems is video surveillance, thanks to the rapid growth of information technology. Particularly prevalent and important in the current world are surveillance cameras, which are almost everywhere. But as the monitoring network continues to grow, more and more people are using surveillance cameras, which not only make life easier but also produce a huge quantity of data that is difficult to store, analyse, and retrieve. Both authorised and illegal people may be seen by an intelligent surveillance system using intelligent video analysis technologies. In this research, we can distinguish between approved and unauthorised persons by applying deep learning algorithm approaches to identify people filmed using camera module. The individual in the video is recognised and recorded using convolutional neural networks (CNN), and the security team will instantly get an email notice with a picture of the unauthorised person if they enter prohibited places.
Keywords
Surveillance, DeepLearning,FaceRecognition,CNN,Monitoring
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