Masaki Nagakawa

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This paper describes a robust context integration model for on-line handwritten Japanese text recognition. Based on string class probability approximation, the proposed method evaluates the likelihood of candidate seg-mentation–recognition paths by combining the scores of character recognition, unary and binary geometric features, as well as linguistic(More)
This paper describes a method for online handwritten Lao character recognition by using dynamic programming matching (DPM). It extracts feature points along the way from pen-down to pen-up, then uses DPM to match those feature points with the feature points for a template pattern of each character class and obtains a similarity for each character class. It(More)
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