Introduction to Bayesian Networks
Introduction to Bayesian Networks
Learning-based Cursive Handwriting Synthesis
IWFHR '02 Proceedings of the Eighth International Workshop on Frontiers in Handwriting Recognition (IWFHR'02)
Inference and Learning in Hybrid Bayesian Networks
Inference and Learning in Hybrid Bayesian Networks
Bayesian Network Modeling of Hangul Characters for On-line Handwriting Recognition
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Handwriting Matching and Its Application to Handwriting Synthesis
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Style-preserving English handwriting synthesis
Pattern Recognition
Biometric technologies and applications
AIAP'07 Proceedings of the 25th conference on Proceedings of the 25th IASTED International Multi-Conference: artificial intelligence and applications
Analysis and modeling of naturalness in handwritten characters
IEEE Transactions on Neural Networks
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In this paper, we propose a new character generationmethod from on-line handwriting recognizers basedon Bayesian networks. On-line handwriting recognizersare trained with handwriting samples from many writers.Then, character shapes are generated from given texts bysearching the most probable input point sequences. SinceBayesian network based classifiers have large number ofparameters for modeling components and their relationships,they generate more natural character shapes thanvarious kinds of hidden Markov models.