Estimating number of letters in on-line cursive words
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Writer adaptation techniques in HMM based Off-Line Cursive Script Recognition
This work presents the application of HMM adaptation techniques to the problem of Off-Line Cursive Script Recognition. Rather than training a new model for each writer, one first creates a unique model with a mixed database and then adapts it for each different writer using his own small dataset. Experiments on a publicly available benchmark database show that an adapted system has an accuracy ...
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تاریخ انتشار 1993