Devanagari Character Segmentation and Recognition

dc.contributor.authorPagare, Gaurav
dc.contributor.supervisorVerma, Karun
dc.date.accessioned2015-07-22T08:25:00Z
dc.date.available2015-07-22T08:25:00Z
dc.date.issued2015-07-22T08:25:00Z
dc.descriptionM.E. (CSED)en
dc.description.abstractMachine and human interaction is very essential in today’s scenario. This interaction would make search engines, social media, artificial intelligence, cognitive computing more interactive and user friendly. Handwriting recognition is the systematic process of identifying the characters, numbers and symbols present in the handwritten document. In the current work, a recognition model for digitizing handwritten Devanagari characters is proposed. Auto associative recognition technique for Devanagari characters and numerals proposed in the current work by using classifier. To solve recognition problem a dynamic model based on the Hopfield neural network is deployed. The model performs operation in parallel and making it, faster and optimal in solving recognition problem.en
dc.format.extent1292951 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/10266/3370
dc.language.isoenen
dc.subjectHandwriting Recogntionen
dc.subjectNatural Language Processingen
dc.subjectHopfield Networken
dc.titleDevanagari Character Segmentation and Recognitionen
dc.typeThesisen

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