• DocumentCode
    1910536
  • Title

    Subspace classifier in reproducing kernel Hilbert space

  • Author

    Tsuda, Koji

  • Author_Institution
    Electrotech. Lab., Ibaraki, Japan
  • Volume
    5
  • fYear
    1999
  • fDate
    1999
  • Firstpage
    3054
  • Abstract
    To improve the performance of subspace classifier, it is effective to reduce the dimensionality of the intersections between subspaces. For this purpose, the feature space is mapped implicitly to a high dimensional reproducing kernel Hilbert space and the subspace classifier is applied in this space. As a result of Hiragana recognition experiment, our classifier outperformed the conventional subspace classifier
  • Keywords
    feature extraction; handwritten character recognition; learning (artificial intelligence); neural nets; pattern classification; Hiragana recognition; dimensionality; feature extraction; handwritten character recognition; kernel Hilbert space; learning; pattern classification; subspace classifier; Hilbert space; Kernel; Laboratories; Pattern recognition; Support vector machine classification; Support vector machines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1999. IJCNN '99. International Joint Conference on
  • Conference_Location
    Washington, DC
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-5529-6
  • Type

    conf

  • DOI
    10.1109/IJCNN.1999.836045
  • Filename
    836045
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1910536