Published In
ELECTRICA
Volume 7 · Issue 1
Pages: 309-313
History
Published Online: February 1, 2007
Copyright © 2007 ELECTRICA
Pelin GORGEL
Computer Engineering Department, Engineering Faculty, Istanbul University, Avcilar, Istanbul, TURKEY
Oguzhan OZTAS
Computer Engineering Department, Engineering Faculty, Istanbul University, Avcilar, Istanbul, TURKEY
GORGEL, P., & OZTAS, O. (2007). HANDWRITTEN CHARACTER RECOGNITION SYSTEM USING ARTIFICIAL NEURAL NETWORKS. ELECTRICA, 7(1), 309–313. Retrieved from https://electricajournal.org/index.php/pub/article/view/407
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Abstract
In this paper, a Handwritten Character Recognition system is designed using Multilayer Feedforward Articial Neural Networks. Backpropagation Learning algorithm is prefered for training of neural network. Training set occures of various Latin characters collected from different people. The characters are presented directly to the network and correctly sized in pre-processing. Recognition percentage of the system is higher than acceptable level. Input datas, network parametres and training period effect the result.
Article Info
Published In
Journal
ELECTRICA
Volume / Issue
Volume 7 · Issue 1
Pages
309-313
History
Published Online
February 1, 2007
Copyright
Copyright (c) 2007 ELECTRICA
Affiliations
Pelin GORGEL
Computer Engineering Department, Engineering Faculty, Istanbul University, Avcilar, Istanbul, TURKEY
Oguzhan OZTAS
Computer Engineering Department, Engineering Faculty, Istanbul University, Avcilar, Istanbul, TURKEY
Cite this Article
GORGEL, P., & OZTAS, O. (2007). HANDWRITTEN CHARACTER RECOGNITION SYSTEM USING ARTIFICIAL NEURAL NETWORKS. ELECTRICA, 7(1), 309–313. Retrieved from https://electricajournal.org/index.php/pub/article/view/407
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