Face recognition using artificial neural networks in parallel architecture

Batyrkhan Omarov, Azizah Suliman, Kaisar Kushibar

Research output: Contribution to journalArticle

11 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)238-248
Number of pages11
JournalJournal of Theoretical and Applied Information Technology
Issue number2
Publication statusPublished - 30 Sep 2016


All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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