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Face recognition using artificial neural networks in parallel architecture

Face detection and recognition is the main aspect for different important areas such as video surveillance, biometrics, interactive game applications, human computer interaction and access control systems. These systems require fast real time detection and recognition with high recognition rate. In...

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Main Authors: Omarov B., Suliman A., Kushibar K.
Other Authors: 57202103462
Format: Article
Published: Asian Research Publishing Network 2023
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spelling my.uniten.dspace-226532023-05-29T14:11:30Z Face recognition using artificial neural networks in parallel architecture Omarov B. Suliman A. Kushibar K. 57202103462 25825739000 57191381849 Face detection and recognition is the main aspect for different important areas such as video surveillance, biometrics, interactive game applications, human computer interaction and access control systems. These systems require fast real time detection and recognition with high recognition rate. In this paper we propose implementation of the Artificial Neural Network by using high performance computing architecture based on Graphics Processing Unit to get face recognition with high accuracy and more speedup. There, we consider a parallel training approach for backpropagation algorithm for face recognition. For the high performance of face recognition it was used Compute Unified Device Architecture (CUDA) on a GPU. The experimental results demonstrate a significant decrease on executing times and greater speedup than serial implementation. � 2005 - 2016 JATIT & LLS. All rights reserved. Final 2023-05-29T06:11:30Z 2023-05-29T06:11:30Z 2016 Article 2-s2.0-84989339650 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84989339650&partnerID=40&md5=5c103fbdf4526516c5a4d2906c7b9b9a https://irepository.uniten.edu.my/handle/123456789/22653 91 2 238 248 Asian Research Publishing Network Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Face detection and recognition is the main aspect for different important areas such as video surveillance, biometrics, interactive game applications, human computer interaction and access control systems. These systems require fast real time detection and recognition with high recognition rate. In this paper we propose implementation of the Artificial Neural Network by using high performance computing architecture based on Graphics Processing Unit to get face recognition with high accuracy and more speedup. There, we consider a parallel training approach for backpropagation algorithm for face recognition. For the high performance of face recognition it was used Compute Unified Device Architecture (CUDA) on a GPU. The experimental results demonstrate a significant decrease on executing times and greater speedup than serial implementation. � 2005 - 2016 JATIT & LLS. All rights reserved.
author2 57202103462
author_facet 57202103462
Omarov B.
Suliman A.
Kushibar K.
format Article
author Omarov B.
Suliman A.
Kushibar K.
spellingShingle Omarov B.
Suliman A.
Kushibar K.
Face recognition using artificial neural networks in parallel architecture
author_sort Omarov B.
title Face recognition using artificial neural networks in parallel architecture
title_short Face recognition using artificial neural networks in parallel architecture
title_full Face recognition using artificial neural networks in parallel architecture
title_fullStr Face recognition using artificial neural networks in parallel architecture
title_full_unstemmed Face recognition using artificial neural networks in parallel architecture
title_sort face recognition using artificial neural networks in parallel architecture
publisher Asian Research Publishing Network
publishDate 2023
_version_ 1806423575007068160
score 13.223943

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