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dc.contributor.authorTIWARI, ANKIT-
dc.date.accessioned2017-09-18T11:28:07Z-
dc.date.available2017-09-18T11:28:07Z-
dc.date.issued2017-07-
dc.identifier.urihttp://dspace.dtu.ac.in:8080/jspui/handle/repository/15973-
dc.description.abstractOCR stands for Optical Character Recognition and is the mechanical or electronic translation of images consisting of text into the editable text. It is mostly used to convert handwritten(taken by scanner or by other means) into text. Human beings recognize many objects in this manner our eyes are the "optical mechanism." But while the brain "sees" the input, the ability to comprehend these signals varies in each person according to many factors. Digitization of text documents is often combined with the process of optical character recognition (OCR). Recognizing a character is a normal and easy work for human beings, but to make a machine or electronic device that does character recognition is a difficult task. Recognizing characters is one of those things which humans do better than the computer and other electronic devices.en_US
dc.language.isoenen_US
dc.relation.ispartofseriesTD-2955;-
dc.subjectOPTICAL CHARACTER RECOGNITIONen_US
dc.subjectNEURAL NETWORKen_US
dc.titleCHARACTER RECOGNITION USING DEEP LEARNING NEURAL NETWORKen_US
dc.typeThesisen_US
Appears in Collections:M.E./M.Tech. Computer Engineering

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