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Found 2 papers, 1 papers with code
Boosting offline handwritten text recognition in historical documents with few labeled lines
In this paper, we face the problem of offline handwritten text recognition (HTR) in historical documents when few labeled samples are available and some of them contain errors in the train set.
Boosting Handwriting Text Recognition in Small Databases with Transfer Learning
We first investigate, for a reduced and fixed number of training samples, 350 lines, how the learning from a large database, the IAM, can be transferred to the learning of the CLC of a reduced database, Washington.
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