This paper discusses a combination of two techniques for improving the recognition accuracy of on-line handwritten character recognition: committee classification and adaptation to the user. A novel adaptive committee structure, namely the class-confidence critic combination (CCCC) scheme, is presented and evaluated. It is shown to be able to improve significantly on its member classifiers. Also the effect of having either more or less diverse sets of member classifiers is considered.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Class-confidence critic combining


    Contributors:
    Aksela, M. (author) / Girdziugas, R. (author) / Laaksonen, J. (author) / Oja, E. (author) / Kangas, J. (author)


    Publication date :

    2002-01-01


    Size :

    410241 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Class-Confidence Critic Combining

    Aksela, M. / Girdziusas, R. / Laaksonen, J. et al. | British Library Conference Proceedings | 2002


    Confidence Evaluation for Combining Diverse Classifiers

    Hao, H. / Liu, C. / Sako, H. et al. | British Library Conference Proceedings | 2003


    Confidence evaluation for combining diverse classifiers

    Hongwei Hao, / Cheng-Lin Liu, / Sako, H. | IEEE | 2003


    The critic

    TIBKAT | 1.1871,3; mehr nicht digitalisiert


    Online Adaptive Critic Flight Control

    Ferrari, S. | Online Contents | 2004