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Training Neural Networks for Reading Handwritten Amounts on Checks
dc.contributor.author | Palacios Hielscher, Rafael | es-ES |
dc.contributor.author | Gupta, Amar | es-ES |
dc.date.accessioned | 2016-01-15T11:28:06Z | |
dc.date.available | 2016-01-15T11:28:06Z | |
dc.date.issued | 2003-09-17 | es_ES |
dc.identifier.uri | http://hdl.handle.net/11531/5684 | |
dc.description | Capítulos en libros | es_ES |
dc.description.abstract | es-ES | |
dc.description.abstract | While reading handwritten text accurately is a difficult task for computers, the conversion of handwritten papers into digital format is necessary for automatic processing. Since most bank checks are handwritten, the number of checks is very high, and manual processing involves significant expenses, many banks are interested in systems that can read check automatically. This paper presents several approaches to improve the accuracy of neural networks used to read unconstrained numerals in the courtesy amount field of bank checks. | en-GB |
dc.format.mimetype | application/pdf | es_ES |
dc.language.iso | en-GB | es_ES |
dc.publisher | Sin editorial (Toulouse, Francia) | es_ES |
dc.rights | es_ES | |
dc.rights.uri | es_ES | |
dc.source | Libro: 2003 IEEE Workshop on Neural Networks for Signal Processing, ISBN:0-7803-8177-7, pp. 607-616, Página inicial: , Página final: | es_ES |
dc.subject.other | Instituto de Investigación Tecnológica (IIT) | es_ES |
dc.title | Training Neural Networks for Reading Handwritten Amounts on Checks | es_ES |
dc.type | info:eu-repo/semantics/bookPart | es_ES |
dc.description.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.rights.accessRights | info:eu-repo/semantics/restrictedAccess | es_ES |
dc.keywords | es-ES | |
dc.keywords | Optical character recognition, neural networks, document imaging, check processing, unconstrained handwritten numerals. | en-GB |
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