• DocumentCode
    2994721
  • Title

    The Research of Printed Character Recognition Based on Neural Network

  • Author

    Shi, Yingqiao ; Fan, Wenbing ; Shi, Guodong

  • Author_Institution
    Sch. of Inf. Eng., Zhengzhou Univ., Zhengzhou, China
  • fYear
    2011
  • fDate
    9-11 Dec. 2011
  • Firstpage
    119
  • Lastpage
    122
  • Abstract
    Firstly, This paper introduces the application status of the artificial neural network technology in the print character recognition, and then elaborated on the technology of Standard BP neural network. By formula derivation, we showed that Standard BP neural Network exists some defects in the application, and then we take the approach by adding a momentum term to improve the Network, and increases the training speed. Secondly, we randomly selecte 200 printed number-characters and 50 printed letter-characters as a sample of the improved BP neural network experiments, the results show that the method of the number-character recognition rate higher than the alphabetic characters, the performance of convergence speed and recognition is better.
  • Keywords
    backpropagation; neural nets; optical character recognition; artificial neural network technology; convergence speed; momentum term; number-character recognition rate; printed character recognition; standard BP neural network; Artificial neural networks; Biological neural networks; Character recognition; Neurons; Training; Vectors; Neural network; Recognition; character;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel Architectures, Algorithms and Programming (PAAP), 2011 Fourth International Symposium on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-1-4577-1808-3
  • Type

    conf

  • DOI
    10.1109/PAAP.2011.23
  • Filename
    6128488