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Face Recognition for Surveillance Systems using SRGAN

Authors: Prof. M. Seshaiah; Prof. Shrishail Math;

Face Recognition for Surveillance Systems using SRGAN

Abstract

Abstract- In this current era, surveillance systems are being installed in all crucial places such as banks, malls, houses and many such places. The main reason for this is security and to achieve this crucial objective, face recognition becomes important. Face recognition is an important factor which becomes one of the factors for growth in technologies such as Computer Vision, Pattern Matching and Artificial Neural Networks. Face recognition has been a major challenge in the field of computer vision since it has to encounter a series of implementations for successful execution of identifying a particular face in the video from a surveillance camera. There are many factors such as light conditions, facial expressions and poor quality of the surveillance device, that affect the implementation of recognizing a face from the image or the video captured by a surveillance system. Hence the images recorded in such conditions require special attention and hence need to be enhanced for better results. The aim of the paper is to provide various methods to provide an efficient facial recognition method with minimal cost and high efficiency. Keywords : Face identification/recognition, surveillance system, computer vision,Pattern Matching

Keywords

Artificial Intelligence, Computer Science, Information System, Information Technology

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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