Machine recognition of hand-printed Japanese characters has been an area of great interest for many years. A major problem of this classification task is the huge number of different characters. Applying standard "state-of-the-art" techniques, such as SVM, to multi-class problems of this kind imposes severe problems of both a conceptual and technical nature: (i) separating one class from all others may be an unnecessarily hard problem; and (ii) solving these subproblems can impose unacceptably high computational costs. In this paper, a new approach to Japanese character recognition is presented that successfully overcomes these shortcomings. It is based on a pairwise coupling procedure for probabilistic two-class kernel classifiers. Experimental results for Hiragana recognition effectively demonstrate that our method attains an excellent level of prediction accuracy while imposing very low computational costs.


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    Title :

    Pairwise coupling for machine recognition of hand-printed Japanese characters


    Contributors:
    Roth, V. (author) / Tsuda, K. (author)


    Publication date :

    2001-01-01


    Size :

    613758 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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