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Abstract: In this paper, we propose a new character generation method from on-line handwriting recognizers based on Bayesian networks. On-line handwriting recognizers are trained with handwriting samples from many writers. Then, character shapes are generated from given texts by searching the most probable input point sequences. Since Bayesian network based classifiers have large number of parameters for modeling components and their relationships, they generate more natural character shapes than various ... (Update)
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BibTeX entry: (Update)
@misc{ network-generation,
author = "With Bayesian Network",
title = "Generation of Handwritten Characters",
url = "citeseer.ist.psu.edu/694839.html" }
Citations (may not include all citations):312 An Introduction to Bayesian Networks (context) - Jensen - 1996
29 An evaluation of motor models of handwriting (context) - Plamondon, Maarse - 1989
19 Dynamical encoding of cursive handwriting - Singer, Tishby - 1994
11 Inference and learning in hybrid bayesian networks - Murphy - 1998
4 The generation of handwriting with delta-lognormal synergies (context) - Plamondon, Guerfali - 1998
4 Handwriting synthesis from handwritten glyphs - Guyon - 1996
3 Learningbased cursive handwriting synthesis - Wang, Wu et al. - 2002
1 Baysian network modeling of character components and their r.. (context) - Cho - 2003
1 Network-based approach to korean handwriting analysis (context) - Sin, Kim - 1998
1 Bayesian network modeling of hangul characters for on-line h.. - Cho, Kim - 2003
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