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dc.contributor.authorKoyuncu, Baki
dc.contributor.authorKoyuncu, Hakan
dc.date.accessioned2019-04-30T09:07:29Z
dc.date.available2019-04-30T09:07:29Z
dc.date.issued2019-03-29
dc.identifier.issn2149-0104
dc.identifier.issn2149-5262
dc.identifier.urihttp://hdl.handle.net/11363/1143
dc.description.abstractAbstract - Handwritten character recognition is an important domain of research with implementation in varied fields. Past and recent works in this field focus on diverse languages to utilize the character recognition in automated data-entry applications. Studies in Deep Neural Network recognize the individual characters in the form of images. The reliance of each recognition, which is provided by the neural network as part of the ranking result, is one of the things used to customize the implementation to the request of the client. Convolutional deep neural network model is reviewed to recognize the handwritten characters in this study. This model, initially, learned a useful set of admittance by using local receptive areas and densely connected network layers are employed for the discernment task. Keywords Handwritten Character Recognition, Deep Neural Network (DNN), Deep Convolutional Neural Network (DCNN).en_US
dc.language.isoengen_US
dc.publisherİstanbul Gelişim Üniversitesi Yayınları / Istanbul Gelisim University Pressen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.subjectResearch Subject Categories::TECHNOLOGYen_US
dc.titleHandwritten Character Recognition by using Convolutional Deep Neural Network; Reviewen_US
dc.typearticleen_US
dc.relation.ispartofInternational Journal of Engineering Technologiesen_US
dc.departmentMühendislik ve Mimarlık Fakültesien_US
dc.identifier.volume5en_US
dc.identifier.issue1en_US
dc.identifier.startpage1en_US
dc.identifier.endpage5en_US
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Yayınıen_US


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