• DocumentCode
    2052206
  • Title

    Bill classification by using the LVQ method

  • Author

    Kosaka, Toshihisa ; Omatu, Sigeru ; Fujinaka, Toru

  • Author_Institution
    Glory Ltd., Himeji, Japan
  • Volume
    3
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    1430
  • Abstract
    For pattern classification problems the neuro-pattern recognition, which is the pattern recognition based on the neural network approach, has been increasingly popular since it can classify various patterns similar to human beings. In this paper we adopt the learning vector quantization (LVQ) method to classify the various bank notes. The reasons to use LVQ are that it can process the unsupervised classification and treat many input data with small computational burdens. We construct the LVQ network to classify the Italian Liras. Compared with a conventional pattern matching technique, which has been adopted as a classification method, the proposed method has shown excellent classification results
  • Keywords
    bank data processing; learning (artificial intelligence); neural nets; pattern classification; vector quantisation; Italian Liras; LVQ algorithm; bank notes; competitive neural network; learning vector quantization; pattern classification; Biological neural networks; Clustering algorithms; Focusing; Humans; Neurons; Pattern classification; Pattern matching; Pattern recognition; Pixel; Size measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics, 2001 IEEE International Conference on
  • Conference_Location
    Tucson, AZ
  • ISSN
    1062-922X
  • Print_ISBN
    0-7803-7087-2
  • Type

    conf

  • DOI
    10.1109/ICSMC.2001.973483
  • Filename
    973483