Top-Down Likelihood Word Image Generation Model for Holistic Word Recognition
DAS '02 Proceedings of the 5th International Workshop on Document Analysis Systems V
A Study on Top-down Word Image Generation for Handwritten Word Recognition
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Off-line cursive script recognition: current advances, comparisons and remaining problems
Artificial Intelligence Review
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A hybrid radial basis function network/hidden Markov model off-line handwritten word recognition system is presented. It is inspired from methods used originally in the field of automatic speech recognition. The hidden Markov model part of the system is in charge of modelling the alignment of letters onto segments produced by a rule-based explicit segmentation process. The role of the radial basis function networks is the estimation of emission probabilities associated to Markov states from the bitmaps of segments. It is shown that this system compares advantageously with a previous version using symbolic features as observations.