• DocumentCode
    3022314
  • Title

    A hierarchical classifier using new support vector machine

  • Author

    Wang, Yu-Chiang ; Casasent, David

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA, USA
  • fYear
    2005
  • fDate
    29 Aug.-1 Sept. 2005
  • Firstpage
    851
  • Abstract
    A binary hierarchical classifier is proposed to solve the multi-class classification problem. We also require rejection of non-target inputs, which produces a very difficult problem. The SVRDM (support vector representation and discrimination machine) classifier is considered at each node in the hierarchy, since it offers good generalization and rejection ability. Using this hierarchical SVRDM classifier with magnitude Fourier transform features, initial recognition and rejection test results on simulated infrared data are excellent.
  • Keywords
    Fourier transforms; pattern classification; support vector machines; Fourier transform; discrimination machine classifier; hierarchical SVRDM classifier; multiclass classification; support vector machine; support vector representation; Classification tree analysis; Face recognition; Fourier transforms; Neural networks; Pattern recognition; Support vector machine classification; Support vector machines; Target recognition; Testing; Voting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Document Analysis and Recognition, 2005. Proceedings. Eighth International Conference on
  • ISSN
    1520-5263
  • Print_ISBN
    0-7695-2420-6
  • Type

    conf

  • DOI
    10.1109/ICDAR.2005.16
  • Filename
    1575665