1 Ocak 2014 Konferans bildirisi Açık Erişim

Aydemir, M. Said; Aydin, Burak; Kaya, Hamza; Karliaga, Ibrahim; Demir, Cemil

Dublin Core

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  <dc:creator>Aydemir, M. Said</dc:creator>
  <dc:creator>Aydin, Burak</dc:creator>
  <dc:creator>Kaya, Hamza</dc:creator>
  <dc:creator>Karliaga, Ibrahim</dc:creator>
  <dc:creator>Demir, Cemil</dc:creator>
  <dc:date>2014-01-01</dc:date>
  <dc:description>In this study, two different Ottoman and Turkish handwritten recognition systems have been developed using Hidden Markov Model (HMM) and Recurrent Neural Network (RNN). The systems are tested in both public use datasets and Civil Registration and Nationality (CRN) dataset.</dc:description>
  <dc:identifier>https://aperta.ulakbim.gov.trrecord/99105</dc:identifier>
  <dc:identifier>oai:zenodo.org:99105</dc:identifier>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>http://www.opendefinition.org/licenses/cc-by</dc:rights>
  <dc:title>TUBITAK TURKISH - OTTOMAN HANDWRITTEN RECOGNITION SYSTEM</dc:title>
  <dc:type>info:eu-repo/semantics/conferencePaper</dc:type>
  <dc:type>publication-conferencepaper</dc:type>
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