• DocumentCode
    1653719
  • Title

    Distortion invariant handwritten digit recognition using adaptive resonance theory (ART) neural net model

  • Author

    Khan, Emdadur R.

  • Author_Institution
    Nat. Semicond., Santa Clara, CA, USA
  • fYear
    1990
  • Firstpage
    1266
  • Abstract
    A distortion- and rotation-invariant handwritten digit recognition scheme using a modified version of the adaptive resonance theory neural network model proposed by S. Grossberg and G. Carpenter (1988) is reported. The scheme is robust. It can be extended to the recognition of other handwritten characters
  • Keywords
    adaptive systems; neural nets; optical character recognition; adaptive resonance theory neural network model; distortion-invariant recognition; handwritten characters; rotation-invariant handwritten digit recognition; Character recognition; Handwriting recognition; Neural networks; Neurons; Reliability theory; Resonance; Robustness; Shape; Subspace constraints; Very large scale integration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics Society, 1990. IECON '90., 16th Annual Conference of IEEE
  • Conference_Location
    Pacific Grove, CA
  • Print_ISBN
    0-87942-600-4
  • Type

    conf

  • DOI
    10.1109/IECON.1990.149319
  • Filename
    149319
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1653719