• DocumentCode
    2226175
  • Title

    Structure of neural networks for industrial character reader

  • Author

    Hata, Seiji ; Seino, K. ; Yagisawa, Akira

  • Author_Institution
    Fac. of Educ., Kagawa Univ., Takamatsu, Japan
  • fYear
    1993
  • fDate
    15-19 Nov 1993
  • Firstpage
    1888
  • Abstract
    Neural networks to recognize industrial characters are required to achieve high reading reliability. To achieve this high reliability, a method to control the structure of a neural network´s hidden layer has been introduced. The method defines the feature extraction functions of neurons in the hidden layer, and preliminary teaching is so constructed that it gives the hidden layer neurons defined properties. After the desired property attached to the hidden layer neurons, the ordinary backpropagation procedure refines the structure of the neural network
  • Keywords
    automatic optical inspection; backpropagation; character recognition; character recognition equipment; feature extraction; neural nets; backpropagation; feature extraction functions; high reading reliability; industrial character reader; neural network´s hidden layer; neural networks; preliminary teaching; Assembly systems; Character recognition; Computer network reliability; Computer science; Inspection; Manufacturing; Neural networks; Neurons; Production; Reliability engineering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics, Control, and Instrumentation, 1993. Proceedings of the IECON '93., International Conference on
  • Conference_Location
    Maui, HI
  • Print_ISBN
    0-7803-0891-3
  • Type

    conf

  • DOI
    10.1109/IECON.1993.339362
  • Filename
    339362