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by Matthias Zimmermann, Roman Bertolami, Horst Bunke
In 17th International Conference on Pattern Recognition
http://www.iam.unibe.ch/~bertolam/publications/rejection_icpr_2004.pdf
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Abstract:
This paper investigates three different rejection strategies for offline handwritten sentence recognition. The rejection strategies are implemented as a postprocessing step of a Hidden Markov Model based text recognition system and are based on confidence measures derived from a list of candidate sentences produced by the recognizer. The better performing confidence measures make use of the fact that the recognizer integrates a word bigram language model. Experimental results on extracted sentences from the IAM database validate the effectiveness of the proposed rejection strategies. 1.
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