• DocumentCode
    1648424
  • Title

    Fast recognition of handwritten digits using pairwise coupling support vector machine

  • Author

    Zeyu, Li ; ShiWei, Tang ; Hao, Wang

  • Author_Institution
    Nat. Lab. on Machine Perception, Peking Univ., Beijing, China
  • Volume
    1
  • fYear
    2002
  • fDate
    6/24/1905 12:00:00 AM
  • Firstpage
    878
  • Lastpage
    883
  • Abstract
    In this paper, a hierarchical structure combining a linear classifier based on the Mahalanobis distance and pairwise coupling (PWC) is proposed to effectively tackle multi-class classification problem. By taking the advantage of the distribution information of the dataset, both the recognition rate and speed are all improved. At the same time, the proposed method can estimate the posterior probabilities of a testing pattern more accurately than the classical PWC in multi-class cases. Experimental results on handwritten digit recognition demonstrate the effectiveness and efficiency of our method
  • Keywords
    handwritten character recognition; learning automata; neural nets; optimisation; pattern classification; probability; Mahalanobis distance; handwritten digit recognition; hierarchical structure; linear classifier; multiple class pattern classification; optimization; pairwise coupling; posterior probability; support vector machine; Computer science; Educational institutions; Face recognition; Handwriting recognition; Laboratories; Support vector machine classification; Support vector machines; Testing; Text recognition; Voting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
  • Conference_Location
    Honolulu, HI
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-7278-6
  • Type

    conf

  • DOI
    10.1109/IJCNN.2002.1005590
  • Filename
    1005590