• DocumentCode
    396680
  • Title

    Classification of the Italian Liras using the LVQ method

  • Author

    Omatu, Sigeru ; Kosaka, Toshihisa ; Teranisi, Masaru

  • Author_Institution
    Osaka Prefectural Univ., Sakai, Japan
  • Volume
    3
  • fYear
    2003
  • fDate
    20-24 July 2003
  • Firstpage
    2212
  • Abstract
    For the pattern classification problems the neuro-pattern recognition which is the pattern recognition based on the neural network approach has been paid an attention since it can classify various patterns like human beings. In this paper, we adopt the learning vector quantization(LVQ) method to classify the various money. The reasons to use the LVQ are that it can process the unsupervised classification and treat many input data with small computational burdens. We will 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; neural nets; pattern classification; unsupervised learning; vector quantisation; Italian Liras classification; LVQ method; LVQ network; bank notes; computational burdens; learning vector quantization; money classification; neural network; pattern classification; unsupervised classification; Biological neural networks; Educational institutions; Humans; Neurons; Office automation; Pattern classification; Pattern matching; Pattern recognition; Pixel; Size measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2003. Proceedings of the International Joint Conference on
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-7898-9
  • Type

    conf

  • DOI
    10.1109/IJCNN.2003.1223752
  • Filename
    1223752