Face Recognition Networks Review and Analysis

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Mahjouri, Mehran | 2022

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Type of Document: Ph.D. Dissertation
Language: Farsi
Document No: 55451 (02)
University: Sharif University of Technology
Department: Mathematical Sciences
Advisor(s): Razvan, Mohammad Reza; Moghadasi, Reza; Kamali Tabrizi, Mostafa
Abstract:
Face recognition, which is one of the most important biometrics, has always been one of the main challenges in many security issues, such as verifying the identity of customers of financial institutions and passengers at the airport, and such issues have many applications in daily life. Face recognition has always been an important issue in computer vision and pattern recognition. Currently, several methods based on deep networks have shown great results in face recognition, among which the following can be mentioned.1.The deep face was introduced by Facebook in 2014; 2.Face-net was presented by Google in 2015 ;3.VGGFace was presented by Oxford University in 2015; 4.Openface was presented by CMU University in 2016.The purpose of this thesis is to study and analyze these methods to check the sen- sitivity of each of them to changes and their resistance to various attacks. In this regard, each model’s feature space will be examined, and the distribution of data in this space will be studied
Keywords:
Face Recognition ; Deep Networks ; Sensitivity Analysis ; Pattern Recognition ; Computer Vision