• DocumentCode
    1298869
  • Title

    Neocognitron: A neural network model for a mechanism of visual pattern recognition

  • Author

    Fukushima, Kazuki ; Miyake, S. ; Ito, Takao

  • Author_Institution
    NHK Broadcasting Sci. Res. Labs., Tokyo, Japan
  • Issue
    5
  • fYear
    1983
  • Firstpage
    826
  • Lastpage
    834
  • Abstract
    A recognition with a large-scale network is simulated on a PDP-11/34 minicomputer and is shown to have a great capability for visual pattern recognition. The model consists of nine layers of cells. The authors demonstrate that the model can be trained to recognize handwritten Arabic numerals even with considerable deformations in shape. A learning-with-a-teacher process is used for the reinforcement of the modifiable synapses in the new large-scale model, instead of the learning-without-a-teacher process applied to a previous model. The authors focus on the mechanism for pattern recognition rather than that for self-organization.
  • Keywords
    digital simulation; neural nets; pattern recognition; visual perception; PDP-11/34 minicomputer; digital simulation; handwritten Arabic numerals; large-scale network; learning-with-a-teacher process; modifiable synapses; neural network model; recognition; reinforcement; visual pattern recognition; visual perception; Biological neural networks; Brain modeling; Computational modeling; Pattern recognition; Shape; Training; Visualization;
  • fLanguage
    English
  • Journal_Title
    Systems, Man and Cybernetics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9472
  • Type

    jour

  • DOI
    10.1109/TSMC.1983.6313076
  • Filename
    6313076