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    block this user An-Ping Li

    Research Fellow

    Beijing 100085, P.R.China

    Offline Recognition of Unconstrained Handwritten . . .

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    This paper presents a system for the oine recognition of large vocabulary unconstrained handwritten texts. The only assumption made about the data is that it is written in English. This allows the application of Statistical Language Models in order to improve the performance of our system. Several experiments have been performed using both single and multiple writer data. Lexica of variable size (from 10,000 to 50,000 words) have been used. The use of language models is shown to improve the accuracy of the system (when the lexicon contains 50,000 words, error rate is reduced by 50% for single writer data and by 25% for multiple writer data). Our approach is described in detail and compared with other methods presented in the literature to deal with the same problem. An experimental setup to correctly deal with unconstrained text recognition is proposed.

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    Title : Offline Recognition of Unconstrained Handwritten . . .
    Abstract : This paper presents a system for the oine recognition of large vocabulary unconstrained handwritten texts. The only assumption made about the data is that it is written in English. This allows the application of Statistical Language Models in order to improve the performance of our system. Several experiments have been performed using both single and multiple writer data. Lexica of variable size (from 10,000 to 50,000 words) have been used. The use of language models is shown to improve the accuracy of the system (when the lexicon contains 50,000 words, error rate is reduced by 50% for single writer data and by 25% for multiple writer data). Our approach is described in detail and compared with other methods presented in the literature to deal with the same problem. An experimental setup to correctly deal with unconstrained text recognition is proposed.
    Subject : unspecified
    Area : Mathematics
    Language : English
    Affiliations
    Url : http://ftp://ftp.idiap.ch/pub/reports/2003/rr03-22.ps.gz
    Doi : 10.1.1.7.4070

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    An-Ping's Peer Evaluation activity

    Emailed by 1
    • Anonymous : 1
    Downloads 668
    Views 528
    Full text requests 9
    Followed by 2

    An-Ping has...

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