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Open AccessArticle

Recognition of Urdu Handwritten Characters Using Convolutional Neural Network

1
Department of Computer Science & IT, The Islamia University of Bahawalpur, Bahawalpur 63100, Pakistan
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L3i Lab, Université of La Rochelle Av. Michel Cŕepeau, 17000 La Rochelle, France
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Department of Information and Communication Engineering, Yeungnam University, Gyeongsan 712-749, Korea
*
Author to whom correspondence should be addressed.
Appl. Sci. 2019, 9(13), 2758; https://doi.org/10.3390/app9132758
Received: 2 June 2019 / Revised: 26 June 2019 / Accepted: 1 July 2019 / Published: 8 July 2019
In the area of pattern recognition and pattern matching, the methods based on deep learning models have recently attracted several researchers by achieving magnificent performance. In this paper, we propose the use of the convolutional neural network to recognize the multifont offline Urdu handwritten characters in an unconstrained environment. We also propose a novel dataset of Urdu handwritten characters since there is no publicly-available dataset of this kind. A series of experiments are performed on our proposed dataset. The accuracy achieved for character recognition is among the best while comparing with the ones reported in the literature for the same task. View Full-Text
Keywords: offline Urdu handwriting; Urdu handwriting recognition; convolutional neural network offline Urdu handwriting; Urdu handwriting recognition; convolutional neural network
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Husnain, M.; Saad Missen, M.M.; Mumtaz, S.; Jhanidr, M.Z.; Coustaty, M.; Muzzamil Luqman, M.; Ogier, J.-M.; Sang Choi, G. Recognition of Urdu Handwritten Characters Using Convolutional Neural Network. Appl. Sci. 2019, 9, 2758.

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