A REAL TIME FACE RECOGNITION SYSTEM USING ALEXNET DEEP CONVOLUTIONAL NETWORK TRANSFER LEARNING MODEL

. In the field of deep learning, facial recognition belongs to the computer vision category. In various applications such as access control system, security, attendance management etc., it has been widely used for authentication and identification purposes. In deep learning, transfer learning is a...

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Autores principales:	LAWRENCE O. OMOTOSHO, IBRAHIM K. OGUNDOYIN, JOSHUA O. OYENIYI, OLUWASHINA A. OYENIRAN
Formato:	article
Lenguaje:	EN
Publicado:	Alma Mater Publishing House "Vasile Alecsandri" University of Bacau 2021
Materias:	transfer learning, convolutional neural network, deep learning Technology T Engineering (General). Civil engineering (General) TA1-2040
Acceso en línea:	https://doaj.org/article/3f1dd446999749d6961a320ceb346ffd
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spelling	oai:doaj.org-article:3f1dd446999749d6961a320ceb346ffd2021-12-02T19:52:40ZA REAL TIME FACE RECOGNITION SYSTEM USING ALEXNET DEEP CONVOLUTIONAL NETWORK TRANSFER LEARNING MODEL2068-75592344-4932https://doaj.org/article/3f1dd446999749d6961a320ceb346ffd2021-10-01T00:00:00Zhttp://www.jesr.ub.ro/1/article/view/277https://doaj.org/toc/2068-7559https://doaj.org/toc/2344-4932 . In the field of deep learning, facial recognition belongs to the computer vision category. In various applications such as access control system, security, attendance management etc., it has been widely used for authentication and identification purposes. In deep learning, transfer learning is a method of using a neural network model that is first trained on a problem similar to the problem that is being solved. The most commonly used face recognition methods are mainly based on template matching, geometric features based, algebraic and deep learning method. The advantage of template matching is that it is easy to implement, and the disadvantage is that it is difficult to deal with the pose and scale changes effectively. The most important issue, regardless of the method used in the face recognition system, is dimensionality and computational complexity, especially when operating on large databases. In this paper, we applied a transfer learning model based on AlexNet Deep convolutional network to develop a real time face recognition system that has a good robustness to face pose and illumination, reduce dimensionality, complexity and improved recognition accuracy. The system has a recognition accuracy of 98.95 %. LAWRENCE O. OMOTOSHOIBRAHIM K. OGUNDOYINJOSHUA O. OYENIYIOLUWASHINA A. OYENIRANAlma Mater Publishing House "Vasile Alecsandri" University of Bacauarticletransfer learning, convolutional neural network, deep learningTechnologyTEngineering (General). Civil engineering (General)TA1-2040ENJournal of Engineering Studies and Research, Vol 27, Iss 2 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	transfer learning, convolutional neural network, deep learning Technology T Engineering (General). Civil engineering (General) TA1-2040
spellingShingle	transfer learning, convolutional neural network, deep learning Technology T Engineering (General). Civil engineering (General) TA1-2040 LAWRENCE O. OMOTOSHO IBRAHIM K. OGUNDOYIN JOSHUA O. OYENIYI OLUWASHINA A. OYENIRAN A REAL TIME FACE RECOGNITION SYSTEM USING ALEXNET DEEP CONVOLUTIONAL NETWORK TRANSFER LEARNING MODEL
description	. In the field of deep learning, facial recognition belongs to the computer vision category. In various applications such as access control system, security, attendance management etc., it has been widely used for authentication and identification purposes. In deep learning, transfer learning is a method of using a neural network model that is first trained on a problem similar to the problem that is being solved. The most commonly used face recognition methods are mainly based on template matching, geometric features based, algebraic and deep learning method. The advantage of template matching is that it is easy to implement, and the disadvantage is that it is difficult to deal with the pose and scale changes effectively. The most important issue, regardless of the method used in the face recognition system, is dimensionality and computational complexity, especially when operating on large databases. In this paper, we applied a transfer learning model based on AlexNet Deep convolutional network to develop a real time face recognition system that has a good robustness to face pose and illumination, reduce dimensionality, complexity and improved recognition accuracy. The system has a recognition accuracy of 98.95 %.
format	article
author	LAWRENCE O. OMOTOSHO IBRAHIM K. OGUNDOYIN JOSHUA O. OYENIYI OLUWASHINA A. OYENIRAN
author_facet	LAWRENCE O. OMOTOSHO IBRAHIM K. OGUNDOYIN JOSHUA O. OYENIYI OLUWASHINA A. OYENIRAN
author_sort	LAWRENCE O. OMOTOSHO
title	A REAL TIME FACE RECOGNITION SYSTEM USING ALEXNET DEEP CONVOLUTIONAL NETWORK TRANSFER LEARNING MODEL
title_short	A REAL TIME FACE RECOGNITION SYSTEM USING ALEXNET DEEP CONVOLUTIONAL NETWORK TRANSFER LEARNING MODEL
title_full	A REAL TIME FACE RECOGNITION SYSTEM USING ALEXNET DEEP CONVOLUTIONAL NETWORK TRANSFER LEARNING MODEL
title_fullStr	A REAL TIME FACE RECOGNITION SYSTEM USING ALEXNET DEEP CONVOLUTIONAL NETWORK TRANSFER LEARNING MODEL
title_full_unstemmed	A REAL TIME FACE RECOGNITION SYSTEM USING ALEXNET DEEP CONVOLUTIONAL NETWORK TRANSFER LEARNING MODEL
title_sort	real time face recognition system using alexnet deep convolutional network transfer learning model
publisher	Alma Mater Publishing House "Vasile Alecsandri" University of Bacau
publishDate	2021
url	https://doaj.org/article/3f1dd446999749d6961a320ceb346ffd
work_keys_str_mv	AT lawrenceoomotosho arealtimefacerecognitionsystemusingalexnetdeepconvolutionalnetworktransferlearningmodel AT ibrahimkogundoyin arealtimefacerecognitionsystemusingalexnetdeepconvolutionalnetworktransferlearningmodel AT joshuaooyeniyi arealtimefacerecognitionsystemusingalexnetdeepconvolutionalnetworktransferlearningmodel AT oluwashinaaoyeniran arealtimefacerecognitionsystemusingalexnetdeepconvolutionalnetworktransferlearningmodel AT lawrenceoomotosho realtimefacerecognitionsystemusingalexnetdeepconvolutionalnetworktransferlearningmodel AT ibrahimkogundoyin realtimefacerecognitionsystemusingalexnetdeepconvolutionalnetworktransferlearningmodel AT joshuaooyeniyi realtimefacerecognitionsystemusingalexnetdeepconvolutionalnetworktransferlearningmodel AT oluwashinaaoyeniran realtimefacerecognitionsystemusingalexnetdeepconvolutionalnetworktransferlearningmodel
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A REAL TIME FACE RECOGNITION SYSTEM USING ALEXNET DEEP CONVOLUTIONAL NETWORK TRANSFER LEARNING MODEL

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