• DocumentCode
    2961101
  • Title

    Self Organizing Maps and bit signature: A study applied on signal language recognition

  • Author

    Neris, Marrony N. ; Silva, Alexandre J. ; Peres, Sarajane M. ; Flores, Franklin C.

  • Author_Institution
    State Univ. of Maringa (UEM), Maringa
  • fYear
    2008
  • fDate
    1-8 June 2008
  • Firstpage
    2934
  • Lastpage
    2941
  • Abstract
    Self organizing map (SOM) is a kind of artificial neural network with a competitive and unsupervised learning. This technique is commonly used to dataset clustering tasks and can be useful in patterns recognition problems. This paper presents an artificial neural network application to signals language recognition problem, where the image representation is given by bit signatures. The recognition results are promising and are presented in this paper. More, some analysis about the combination ldquoSOM + bit signaturerdquo improved our understanding about the characteristics of the LIBRAS signals and the conclusions are also listed in this paper.
  • Keywords
    gesture recognition; image representation; pattern clustering; self-organising feature maps; unsupervised learning; LIBRAS signals; artificial neural network; bit signature; competitive learning; dataset clustering; image representation; patterns recognition; self organizing maps; signal language recognition; unsupervised learning; Algorithm design and analysis; Artificial neural networks; Deafness; Image recognition; Image representation; Neurons; Pattern recognition; Self organizing feature maps; Signal analysis; Unsupervised learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1098-7576
  • Print_ISBN
    978-1-4244-1820-6
  • Electronic_ISBN
    1098-7576
  • Type

    conf

  • DOI
    10.1109/IJCNN.2008.4634211
  • Filename
    4634211