Parallel backpropagation neural network training for face recognition

Batyrkhan Omarov, Azizah Suliman, Anton Tsoy

Research output: Contribution to journalArticle

8 Citations (Scopus)


In this paper, we describe implementation of ANN training process using backpropagation learning algorithm for exploiting the high performance SIMD architecture of GPU using CUDA. We also compare sequential and parallel algorithm execution times and conducted speedup analysis for both the methods. The simulation results demonstrate a significant decrease on executing times and greater speedup than serial implementation of training and learning processes. All due to the parallel algorithm and use of the GPU, the training time for huge set of images get reduced significantly increasing the accuracy rate of face recognition.

Original languageEnglish
Pages (from-to)801-808
Number of pages8
JournalFar East Journal of Electronics and Communications
Issue number4
Publication statusPublished - Dec 2016

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Electrical and Electronic Engineering

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