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Volumn 2005, Issue , 2005, Pages 516-520

Statistical language models for on-line handwritten sentence recognition

Author keywords

[No Author keywords available]

Indexed keywords

INFORMATION TECHNOLOGY; MATHEMATICAL MODELS; ONLINE SYSTEMS; OPTIMAL SYSTEMS; STATISTICAL METHODS;

EID: 33947433230     PISSN: 15205363     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDAR.2005.220     Document Type: Conference Paper
Times cited : (10)

References (14)
  • 1
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    • Integration of an On-line Handwriting Recognition System in a Smart Phone Device
    • E. Anquetil and H. Bouchereau. Integration of an On-line Handwriting Recognition System in a Smart Phone Device. In 16th ICPR, pages 192-195, 2002.
    • (2002) 16th ICPR , pp. 192-195
    • Anquetil, E.1    Bouchereau, H.2
  • 3
    • 18044398432 scopus 로고    scopus 로고
    • Lexical Post-Processing Optimization for Handwritten Word Recognition
    • S. Carbonnel and E. Anquetil. Lexical Post-Processing Optimization for Handwritten Word Recognition. In 7th ICDAR, pages 477-481, 2003.
    • (2003) 7th ICDAR , pp. 477-481
    • Carbonnel, S.1    Anquetil, E.2
  • 4
    • 18044384414 scopus 로고    scopus 로고
    • Lexicon Organization and String Edit Distance Learning for Lexical Post-Processing in Handwriting Recognition
    • S. Carbonnel and E. Anquetil. Lexicon Organization and String Edit Distance Learning for Lexical Post-Processing in Handwriting Recognition. In 9th IWFHR, pages 462-467, 2004.
    • (2004) 9th IWFHR , pp. 462-467
    • Carbonnel, S.1    Anquetil, E.2
  • 5
    • 0003396042 scopus 로고    scopus 로고
    • An Empirical Study of Smoothing Techniques for Language Modeling
    • Technical Report TR-10-98, Harvard University
    • S. Chen and J. Goodman. An Empirical Study of Smoothing Techniques for Language Modeling. Technical Report TR-10-98, Harvard University, 1998.
    • (1998)
    • Chen, S.1    Goodman, J.2
  • 8
    • 0035247074 scopus 로고    scopus 로고
    • Using a Statistical Language Model to Improve the Performance of an HMM-Based Cursive Handwriting Recognition System
    • U.-V. Marti and H. Bunke. Using a Statistical Language Model to Improve the Performance of an HMM-Based Cursive Handwriting Recognition System. IJPRAI, 15(1):65-90, 2001.
    • (2001) IJPRAI , vol.15 , Issue.1 , pp. 65-90
    • Marti, U.-V.1    Bunke, H.2
  • 9
    • 33947261394 scopus 로고    scopus 로고
    • Sentence Recognition through Hybrid Neuro-Markovian Modeling
    • S. Marukatat. Sentence Recognition through Hybrid Neuro-Markovian Modeling. In 6th ICDAR, pages 731-737, 2001.
    • (2001) 6th ICDAR , pp. 731-737
    • Marukatat, S.1
  • 10
    • 10044263700 scopus 로고    scopus 로고
    • N-Gram and N-Class Models for On Line Handwriting Recognition
    • F. Perraud, C. Viard-Gaudin, E. Morin, and P.-M. Lallican. N-Gram and N-Class Models for On Line Handwriting Recognition. In 7th ICDAR, pages 1053-1059, 2003.
    • (2003) 7th ICDAR , pp. 1053-1059
    • Perraud, F.1    Viard-Gaudin, C.2    Morin, E.3    Lallican, P.-M.4
  • 12
    • 84891308106 scopus 로고    scopus 로고
    • SRILM - An Extensible Language Modeling Toolkit
    • A. Stolcke, SRILM - An Extensible Language Modeling Toolkit. In 7th ICSLP, pages 901-904, 2002.
    • (2002) 7th ICSLP , pp. 901-904
    • Stolcke, A.1
  • 13
    • 3042527199 scopus 로고    scopus 로고
    • Offline Recognition of Unconstrained Handwritten Texts using HMMs and Statistical Language Models
    • A. Vinciarelli, S. Bengio, and H. Bunke. Offline Recognition of Unconstrained Handwritten Texts using HMMs and Statistical Language Models. IEEE Transactions on PAMI, 26(6):709-720, 2004.
    • (2004) IEEE Transactions on PAMI , vol.26 , Issue.6 , pp. 709-720
    • Vinciarelli, A.1    Bengio, S.2    Bunke, H.3
  • 14
    • 18044387782 scopus 로고    scopus 로고
    • N-Gram Language Models for Offline Handwritten Text Recognition
    • M. Zimmermann and H. Bunke. N-Gram Language Models for Offline Handwritten Text Recognition. In 9th IWFHR, pages 203-208, 2004.
    • (2004) 9th IWFHR , pp. 203-208
    • Zimmermann, M.1    Bunke, H.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.