• DocumentCode
    324550
  • Title

    Neocognitron with improved bend-extractors

  • Author

    Fukushima, Kunihiko ; Kimura, Eiji ; Shouno, Hayaru

  • Author_Institution
    Graduate Sch. of Eng. Sci., Osaka Univ., Japan
  • Volume
    2
  • fYear
    1998
  • fDate
    4-9 May 1998
  • Firstpage
    1172
  • Abstract
    We (1988) have reported previously that the performance of a neocognitron can be improved by a built-in bend-extracting layer. The conventional bend-extracting layer can detect bend points and end points of lines correctly, but not always crossing points of lines. This paper discusses that an introduction of a mechanism of disinhibition can make the bend-extracting layer detect not only bend points and end points but also crossing points of lines correctly. A neocognitron with this improved bend-extracting layer can recognize handwritten digits in the real world with a recognition rate of 98%
  • Keywords
    character recognition; edge detection; feature extraction; feedforward neural nets; bend points; bend-extracting layer; crossing points; end points; feature extraction; handwritten digit recognition; line detection; multilayer neural networks; neocognitron; Data mining; Handwriting recognition; Pattern recognition; Robustness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on
  • Conference_Location
    Anchorage, AK
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-4859-1
  • Type

    conf

  • DOI
    10.1109/IJCNN.1998.685939
  • Filename
    685939