• DocumentCode
    353236
  • Title

    Classification of the Italian liras using the LVQ method

  • Author

    Kosaka, Toshihisa ; Omatu, Sigeru

  • Author_Institution
    Glory TD Himeji, Japan
  • Volume
    3
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    145
  • 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 kinds of 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
    financial data processing; image classification; learning (artificial intelligence); neural nets; office automation; vector quantisation; Italian lira classification; LVQ method; banknotes; learning vector quantization; money; neural network; pattern classification; pattern recognition; Biological neural networks; Clustering algorithms; Focusing; Humans; Neurons; Pattern classification; Pattern matching; Pattern recognition; Pixel; Size measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on
  • Conference_Location
    Como
  • ISSN
    1098-7576
  • Print_ISBN
    0-7695-0619-4
  • Type

    conf

  • DOI
    10.1109/IJCNN.2000.861295
  • Filename
    861295