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http://hdl.handle.net/20.500.12358/25059
TitleOiahcr: online isolated arabic handwritten character recognition using neural network.
Untitled
Abstract

In this paper, an online isolated Arabic handwritten character recognition system is introduced. The system can be adapted to achieve the demands of hand-held and digital tablet applications. To achieve this goal, despite of single neural networks, four neural networks are used, one for each cluster of characters. Feed forward back propagation neural networks are used in classification process. This approach is employed as classifiers due to the low computation overhead during training and recall process. The system recognizes on-line isolated Arabic character and achieves an accuracy rate 9٥. 7% from untrained writers and 99.1% for trained writers.

Authors
Alijla, Basem O
Abu Kwaik, Kathrein
TypeJournal Article
Date2012
Subjects
feature extraction
feature selection
feed forward neural networks
optical character recognition
back propagation
classification
Published inInt. Arab J. Inf. Technol.
SeriesVolume: 9, Number: 4
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  • Staff Publications- Faculty of Information Technology [195]
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The institutional repository of the Islamic University of Gaza was established as part of the ROMOR project that has been co-funded with support from the European Commission under the ERASMUS + European programme. This publication reflects the views only of the author, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

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The institutional repository of the Islamic University of Gaza was established as part of the ROMOR project that has been co-funded with support from the European Commission under the ERASMUS + European programme. This publication reflects the views only of the author, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

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