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Face Recognition for Surveillance Systems using SRGAN

Title: Face Recognition for Surveillance Systems using SRGAN
Authors: Prof. M. Seshaiah; Prof. Shrishail Math
Publisher Information: Zenodo
Publication Year: 2020
Collection: Zenodo
Subject Terms: Computer Science; Information Technology; Information System; Artificial Intelligence
Description: 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
Document Type: article in journal/newspaper
Language: English
Relation: https://zenodo.org/communities/ijcsis/; https://zenodo.org/records/4428201; oai:zenodo.org:4428201; https://doi.org/10.5281/zenodo.4428201
DOI: 10.5281/zenodo.4428201
Availability: https://doi.org/10.5281/zenodo.4428201; https://zenodo.org/records/4428201
Rights: Creative Commons Attribution 4.0 International ; cc-by-4.0 ; https://creativecommons.org/licenses/by/4.0/legalcode
Accession Number: edsbas.D49DF967
Database: BASE