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Face recognition using artificial neural networks in parallel architecture

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dc.citedby13
dc.contributor.authorOmarov B.en_US
dc.contributor.authorSuliman A.en_US
dc.contributor.authorKushibar K.en_US
dc.contributor.authorid57202103462en_US
dc.contributor.authorid25825739000en_US
dc.contributor.authorid57191381849en_US
dc.date.accessioned2023-05-29T06:11:30Z
dc.date.available2023-05-29T06:11:30Z
dc.date.issued2016
dc.description.abstractFace 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.en_US
dc.description.natureFinalen_US
dc.identifier.epage248
dc.identifier.issue2
dc.identifier.scopus2-s2.0-84989339650
dc.identifier.spage238
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84989339650&partnerID=40&md5=5c103fbdf4526516c5a4d2906c7b9b9a
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/22653
dc.identifier.volume91
dc.publisherAsian Research Publishing Networken_US
dc.sourceScopus
dc.sourcetitleJournal of Theoretical and Applied Information Technology
dc.titleFace recognition using artificial neural networks in parallel architectureen_US
dc.typeArticleen_US
dspace.entity.typePublication
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