Recognition of Urdu Handwritten Characters Using Convolutional Neural Network

被引:30
作者
Husnain, Mujtaba [1 ]
Missen, Malik Muhammad Saad [1 ]
Mumtaz, Shahzad [1 ]
Jhanidr, Muhammad Zeeshan [1 ]
Coustaty, Mickael [2 ]
Luqman, Muhammad Muzzamil [2 ]
Ogier, Jean-Marc [2 ]
Choi, Gyu Sang [3 ]
机构
[1] Islamia Univ Bahawalpur, Dept Comp Sci & IT, Bahawalpur 63100, Pakistan
[2] Univ La Rochelle, L3i Lab, Ave Michel Crepeau, F-17000 La Rochelle, France
[3] Yeungnam Univ, Dept Informat & Commun Engn, Gyongsan 712749, South Korea
来源
APPLIED SCIENCES-BASEL | 2019年 / 9卷 / 13期
基金
新加坡国家研究基金会;
关键词
offline Urdu handwriting; Urdu handwriting recognition; convolutional neural network; SCRIPT;
D O I
10.3390/app9132758
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
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.
引用
收藏
页数:21
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