A novel handwritten Turkish letter recognition model based on convolutional neural network

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dc.authoridKabakus, Abdullah Talha/0000-0003-2181-4292
dc.contributor.authorKabakus, Abdullah Talha
dc.contributor.authorErdogmus, Pakize
dc.date.accessioned2021-12-01T18:46:57Z
dc.date.available2021-12-01T18:46:57Z
dc.date.issued2021
dc.department[Belirlenecek]en_US
dc.description.abstractConvolutional neural networks have provided state-of-the-art solutions for many subfields of computer vision. While there exist many studies in the literature for several languages, studies for handwritten Turkish character recognition lack in the research field. To this end, we propose a novel handwritten Turkish letter recognition model based on a convolutional neural network. Since, to the best of our knowledge, there do not exist any publicly available handwritten Turkish letters datasets, we constructed a handwritten Turkish letters dataset that consists of 25,875 samples. To compare the performance of the proposed model with the related work, three state-of-the-art models, namely, VGG19, InceptionV3, and Xception, were utilized through the transfer learning technique. When these models were evaluated on the handwritten Turkish letter dataset, the proposed model's accuracy was calculated as high as 96.07% which was higher than the benchmark models. To measure the generalization ability of the proposed model, it was evaluated on a gold standard dataset, namely, EMNIST, and has achieved an accuracy of 80.54% which was higher than the benchmark models. Finally, the proposed model was trained and evaluated on the EMNIST dataset and it has achieved an accuracy of 94.61% which outperformed the related work.en_US
dc.identifier.doi10.1002/cpe.6429
dc.identifier.issn1532-0626
dc.identifier.issn1532-0634
dc.identifier.issue21en_US
dc.identifier.scopus2-s2.0-85106569509en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.urihttps://doi.org/10.1002/cpe.6429
dc.identifier.urihttps://hdl.handle.net/20.500.12684/10072
dc.identifier.volume33en_US
dc.identifier.wosWOS:000655749200001en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherWileyen_US
dc.relation.ispartofConcurrency And Computation-Practice & Experienceen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectconvolutional neural networken_US
dc.subjecthandwrittenen_US
dc.subjectletter recognitionen_US
dc.subjectTurkish letter recognitionen_US
dc.titleA novel handwritten Turkish letter recognition model based on convolutional neural networken_US
dc.typeArticleen_US

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