Face Detection & Recognition using Tensor Flow: A Review

INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY

View Publication Info
 
 
Field Value
 
Title Face Detection & Recognition using Tensor Flow: A Review
 
Creator Chawla, Ishaan
 
Subject Face recognition
machine learning
tensorflow
Face detection
 
Description Face recognition has become a popular topic of research recently due to increases in demand for security as well as the rapid development of mobile devices. There are many applications which face recognition can be applied to such as access control, identity verification, security systems, surveillance systems, and social media networks. Access control includes offices, computers, phones, ATMs, etc. Most of these forms currently do not use face recognition as the standard form of granting entry, but with advancing technologies in computers along with more refined algorithms, facial recognition is gaining some traction in replacing passwords and fingerprint scanners. Ever since the events of 9/11 there has been a more concerned emphasis on developing security systems to ensure the safety of innocent citizens. Namely in places such as airports and border crossings where identification verification is necessary, face recognition systems potentially have the ability to mitigate the risk and ultimately prevent future attacks from occurring. As for surveillance systems, the same point can be made if there are criminals on the loose. Surveillance cameras with face recognition abilities can aide in efforts of finding these individuals. Alternatively, these same surveillance systems can also help identify the whereabouts of missing persons, although this is dependent on robust facial recognition algorithms as well as a fully developed database of faces. And lastly, facial recognition has surfaced in social media applications on platforms such as Facebook which suggest users to tag friends who have been identified in pictures. It is clear that there are many applications the uses for facial recognition systems. In general, the steps to achieve this are the following: face detection, feature extraction, and lastly training a model.
 
Publisher KHALSA PUBLICATIONS
 
Date 2018-11-06
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier http://cirworld.com/index.php/ijct/article/view/7924
10.24297/ijct.v18i0.7924
 
Source INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY; Vol 18; 7381-7388
2277-3061
 
Language eng
 
Relation http://cirworld.com/index.php/ijct/article/view/7924/7532
 

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