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Monday, April 14, 2014

NEURAL NETWORK ARCHITECTURE FOR RECOGNITION OF RUNNING HANDWRITING




ABSTRACT

Handwriting recognition has been a problem that computers are not efficient at. This is obviously due to the varying writing styles that exist. Today, efficient handwriting recognition is limited to ones, using hardware like light pens wherein the strokes are directly detected and the character is recognized.  But if you want to convert a handwritten document to digital text, we have to extract the characters and then recognize the extracted character. But the problem with this approach is that there are not many algorithms that could efficiently extract characters from a sentence. Therefore character recognition using software is still not as efficient as it could be.

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