文章基本信息

标题：FACE RECOGNITION USING ARTIFICIAL NEURAL NETWORKS IN PARALLEL ARCHITECTURE
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作者：BATYRKHAN OMAROV ; AZIZAH SULIMAN ; KAISAR KUSHIBAR 等
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2016
卷号：91
期号：2
出版社：Journal of Theoretical and Applied
摘要：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.
关键词：Artificial Neural Networks; CUDA; Face recognition; GPU; Parallel Computing