Backpropogation Neural Networks to Recognize Isolated Digits
| dc.contributor.advisor | Vasantha Kalyani David | |
| dc.contributor.author | M Dharani | |
| dc.date.accessioned | 2016-12-31T20:51:12Z | |
| dc.date.available | 2016-12-31T20:51:12Z | |
| dc.date.issued | 2010-07 | |
| dc.department | Computer Science | en_US |
| dc.description.abstract | Optical Character Recognition is a field of research that has attracted several researchers for the past several decades. Recognizing handwritten characters pose several challenges, like different style of writing, pen depth and thickness and quality of the scanned handwritten image. Digit recognition, a sub field of character recognition, is the art of recognizing numbers from handwritten images. They are used in various application areas like bank (cheque number recognifion), vehicle tracking (license plate recognition), and Postal Zipcode(post office). | en_US |
| dc.identifier.uri | https://ir.avinuty.ac.in/handle/avu/767 | |
| dc.lang | English | en_US |
| dc.title | Backpropogation Neural Networks to Recognize Isolated Digits | en_US |
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