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OCR systems based on neural network

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dc.title OCR systems based on neural network en Pálka, Jan Pálka, Jiří
dc.relation.ispartof Annals of DAAAM and Proceedings of the International DAAAM Symposium
dc.identifier.issn 1726-9679 OCLC, Ulrich, Sherpa/RoMEO, JCR
dc.identifier.isbn 9783901509834 2011
dc.citation.spage 555
dc.citation.epage 556
dc.event.title Annals of DAAAM for 2011 and 22nd International DAAAM Symposium Intelligent Manufacturing and Automation: Power of Knowledge and Creativity""
dc.event.location Vienna
utb.event.state-en Austria
utb.event.state-cs Rakousko
dc.event.sdate 2011-11-23
dc.event.edate 2011-11-26
dc.type conferenceObject
dc.language.iso en
dc.publisher Danube Adria Association for Automation and Manufacturing, DAAAM
dc.subject Hand-written text en
dc.subject MNIST en
dc.subject Neural network en
dc.subject OCR en
dc.subject Recognition en
dc.description.abstract This paper deals with the recognition of handwritten text. It is mainly discussing improving nowadays OCR systems. In detail is this article focused on the possibilities of implementing the neocognitron network in this improvement. Next part deals with the problems of document processing, recognition of individual characters and subsequent search for whole words against the dictionary. Main goal of this work is to invent new principles in the field of processing hand written text especially focused on text with language specifics like diacritics. en
utb.faculty Faculty of Applied Informatics
utb.identifier.rivid RIV/70883521:28140/11:43866451!RIV12-MSM-28140___
utb.identifier.obdid 43866559
utb.identifier.scopus 2-s2.0-84904291772
utb.source d-scopus 2015-06-29T11:54:17Z 2015-06-29T11:54:17Z
utb.contributor.internalauthor Pálka, Jan
utb.contributor.internalauthor Pálka, Jiří
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