DocumentCode :
2971797
Title :
The Application of optical character recognition for mobile device via artificial neural networks with negative correlation learning algorithm
Author :
Kir, Burcu ; Oz, Cemil ; Gulbag, Ali
Author_Institution :
Comput. Eng. Dept., Kocaeli Univ., Kocaeli, Turkey
fYear :
2013
fDate :
7-9 Nov. 2013
Firstpage :
220
Lastpage :
223
Abstract :
In this study, optical character recognition (OCR) was carried out by using artificial neural network. Negative correlation learning (NCL) method was used to teach artificial neural network. Negative correlation learning, which trains artificial neural networks in groups instead of teaching them individually, is a new technique. By teaching different individual networks as only one network, different parts can be taught at the same time and with this feature teaching will be better and teaching time will be shorter. In this study, image taken with mobile phone were partitioned by processing optical character recognition techniques and their properties were determined. After these letters´ images was classified and converted into text by using artificial neural network ensemble which were taught by negative correlation learning respectively. This system work successfully.
Keywords :
image classification; learning (artificial intelligence); mobile computing; mobile handsets; neural nets; optical character recognition; NCL method; OCR; artificial neural network ensemble; artificial neural network training; feature teaching; letter image classification; mobile device; mobile phone; negative correlation learning algorithm; optical character recognition; Artificial neural networks; Character recognition; Correlation; Mobile handsets; Optical character recognition software; Optical imaging; Training; Artificial Neural Network; Negative Correlation Learning; Optical Character Recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electronics, Computer and Computation (ICECCO), 2013 International Conference on
Conference_Location :
Ankara
Type :
conf
DOI :
10.1109/ICECCO.2013.6718268
Filename :
6718268
Link To Document :
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