Recognition of Urdu Handwritten Characters Using Convolutional Neural Network

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 handwritt...

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Detalles Bibliográficos
Autores principales: Mujtaba Husnain, Malik Muhammad Saad Missen, Shahzad Mumtaz, Muhammad Zeeshan Jhanidr, Mickaël Coustaty, Muhammad Muzzamil Luqman, Jean-Marc Ogier, Gyu Sang Choi
Formato: Artículo
Lenguaje:English
Publicado: MDPI AG 2019-07-01
Colección:Applied Sciences
Materias:
Acceso en línea:https://www.mdpi.com/2076-3417/9/13/2758
Descripción
Sumario: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.
ISSN:2076-3417