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Recognition of Urdu Handwritten Characters Using Convolutional Neural Network
by
Coustaty, Mickaël
, Ogier, Jean-Marc
, Sang Choi, Gyu
, Saad Missen, Malik Muhammad
, Jhanidr, Muhammad Zeeshan
, Muzzamil Luqman, Muhammad
, Husnain, Mujtaba
, Mumtaz, Shahzad
in
Accuracy
/ Artificial Intelligence
/ Computer Science
/ Computer Vision and Pattern Recognition
/ convolutional neural network
/ Document and Text Processing
/ Language
/ Literature reviews
/ Neural and Evolutionary Computing
/ Neural networks
/ offline Urdu handwriting
/ Pattern recognition
/ Researchers
/ Urdu handwriting recognition
/ Writers
2019
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Recognition of Urdu Handwritten Characters Using Convolutional Neural Network
by
Coustaty, Mickaël
, Ogier, Jean-Marc
, Sang Choi, Gyu
, Saad Missen, Malik Muhammad
, Jhanidr, Muhammad Zeeshan
, Muzzamil Luqman, Muhammad
, Husnain, Mujtaba
, Mumtaz, Shahzad
in
Accuracy
/ Artificial Intelligence
/ Computer Science
/ Computer Vision and Pattern Recognition
/ convolutional neural network
/ Document and Text Processing
/ Language
/ Literature reviews
/ Neural and Evolutionary Computing
/ Neural networks
/ offline Urdu handwriting
/ Pattern recognition
/ Researchers
/ Urdu handwriting recognition
/ Writers
2019
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Recognition of Urdu Handwritten Characters Using Convolutional Neural Network
by
Coustaty, Mickaël
, Ogier, Jean-Marc
, Sang Choi, Gyu
, Saad Missen, Malik Muhammad
, Jhanidr, Muhammad Zeeshan
, Muzzamil Luqman, Muhammad
, Husnain, Mujtaba
, Mumtaz, Shahzad
in
Accuracy
/ Artificial Intelligence
/ Computer Science
/ Computer Vision and Pattern Recognition
/ convolutional neural network
/ Document and Text Processing
/ Language
/ Literature reviews
/ Neural and Evolutionary Computing
/ Neural networks
/ offline Urdu handwriting
/ Pattern recognition
/ Researchers
/ Urdu handwriting recognition
/ Writers
2019
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Recognition of Urdu Handwritten Characters Using Convolutional Neural Network
Journal Article
Recognition of Urdu Handwritten Characters Using Convolutional Neural Network
2019
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Overview
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.
Publisher
MDPI AG,Multidisciplinary digital publishing institute (MDPI)
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