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Deep Learning Convolutional Neural Network for Face Recognition: A Review

Rondik J.Hassan and Adnan Abdulazeez
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Rondik J.Hassan: Information Technology Department, Akre Technical College of Informatics, Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq

International Journal of Science and Business, 2021, vol. 5, issue 2, 114-127

Abstract: Face recognition is increasingly being used for solving various social-problems such as personal protection and authentication. As with other widely used biometric applications, facial recognition is a biometric instrument such as iris recognition, vein pattern recognition, and fingerprint recognition. Facial recognition identifies a person based on certain aspects of his physiology. Deep Learning (DL) is a branch of machine learning (ML) that can be used in image processing and pattern recognition to solve multiple problems, one of the applications is face recognition. With the advancement of deep learning, Convolution Neural Network (CNN) based facial recognition technology has been the dominant approach adopted in the field of face recognition. The purpose of this paper is to provide a review of face recognition approaches. Furthermore, the details of each paper, such as used datasets, algorithms, architecture, and achieved results are summarized and analyzed comprehensively.

Keywords: Face Recognition; Machine Learning; Deep Learning; Convolution Neural Network; Feature Extraction; Feature Matching (search for similar items in EconPapers)
Date: 2021
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Handle: RePEc:aif:journl:v:5:y:2021:i:2:p:114-127