Implementation of Deep Neural Network on Image Classification

  • Rui Zhong
    The Graduate School of Library, Information and Media Studies, University of Tsukuba
  • Taro Tezuka
    The Graduate School of Library, Information and Media Studies, University of Tsukuba

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Description

In this research we implemented a scalable deep convolutional neural network based on GPU accelerating techniques, optimized the network architecture on GPU architecutre and reduced the training time by organizing device memory to taking advantages of parallel memory access. We adopted back propagation with limited kernel functions to get higher efficiency. Also we experiment on how learning rate parameters effect the deep network. Experiments on all cases of MNIST training and testing takes less than 15 minutes with an acceptable recognition rate.

Journal

  • IPSJ SIG Notes

    IPSJ SIG Notes 2014 (7), 1-7, 2014-06-18

    Information Processing Society of Japan (IPSJ)

Details 詳細情報について

  • CRID
    1573105977763234944
  • NII Article ID
    110009795485
  • NII Book ID
    AN10505667
  • ISSN
    09196072
  • Text Lang
    en
  • Data Source
    • CiNii Articles

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