• DocumentCode
    1586154
  • Title

    A Multi-layer Quantum Neural Networks Recognition System for Handwritten Digital Recognition

  • Author

    Zhu, Daqi ; Wu, Rushi

  • Author_Institution
    Shanghai Maritime Univ., Shanghai
  • Volume
    1
  • fYear
    2007
  • Firstpage
    718
  • Lastpage
    722
  • Abstract
    In this paper, a handwritten digital recognition system based on multi-level transfer function quantum neural networks (QNN) and multi-layer classifiers is proposed. The recognition system proposed consists of two layer sub-classifiers, namely first-layer QNN coarse classifier and second-layer QNN numeral pairs classifier. Handwritten digital recognition experiments are performed by using data from MNIST database. Experiment results indicate the proposed QNN recognition system achieves excellent performance in terms of recognition rates and recognition reliability, and at the same time show the superiority and potential of QNN in solving pattern recognition problems.
  • Keywords
    handwritten character recognition; neural nets; handwritten digital recognition; multi-layer classifiers; multi-layer quantum neural networks recognition system; Artificial neural networks; Feedforward neural networks; Handwriting recognition; Multi-layer neural network; Neural networks; Neurons; Pattern recognition; Transfer functions; Uncertainty; Weather forecasting; multi-layer classifier; multi-level transfer function; pattern recognition.; quantum neural network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation, 2007. ICNC 2007. Third International Conference on
  • Conference_Location
    Haikou
  • Print_ISBN
    978-0-7695-2875-5
  • Type

    conf

  • DOI
    10.1109/ICNC.2007.70
  • Filename
    4344285