期刊
APPLIED SCIENCES-BASEL
卷 9, 期 13, 页码 -出版社
MDPI
DOI: 10.3390/app9132758
关键词
offline Urdu handwriting; Urdu handwriting recognition; convolutional neural network
类别
资金
- Ministry of Trade, Industry & Energy (MOTIE, Korea) under the Industrial Technology Innovation Program [10063130]
- Basic Science Research Program through the National Research Foundation of Korea (NRF) - Ministry of Education [NRF-2019R1A2C1006159]
- MSIT (Ministry of Science and ICT), Korea, under the ITRC (Information Technology Research Center) support program [IITP-2019-2016-0-00313]
- 2018 Yeungnam University Research Grant
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.
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