Handwritten Character Recognition by using Convolutional Deep Neural Network; Review
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Tarih
2019-03-29
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
İstanbul Gelişim Üniversitesi Yayınları / Istanbul Gelisim University Press
Erişim Hakkı
info:eu-repo/semantics/openAccess
Attribution-NonCommercial-NoDerivs 3.0 United States
Attribution-NonCommercial-NoDerivs 3.0 United States
Özet
Abstract - 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).
Açıklama
Anahtar Kelimeler
Research Subject Categories::TECHNOLOGY
Kaynak
International Journal of Engineering Technologies
WoS Q Değeri
Scopus Q Değeri
Cilt
5
Sayı
1
