Multiple convolutional neural network training for Bangla handwritten numeral recognition

Akhand, M. A. H and Ahmed, Mahtab and Rahman, M.M. Hafizur (2016) Multiple convolutional neural network training for Bangla handwritten numeral recognition. In: 6th International Conference on Computer and Communication Engineering (ICCCE 2016), 25th-27th July 2016, Kuala Lumpur.

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Abstract

Recognition of handwritten numerals has gained much interest in recent years due to its various application potentials. The progress of handwritten Bangla numeral is well behind Roman, Chinese and Arabic scripts although it is a major language in Indian subcontinent and is the first language of Bangladesh. Handwritten numeral classification is a high-dimensional complex task and existing methods use distinct feature extraction techniques and various classification tools in their recognition schemes. Recently, convolutional neural network (CNN) is found efficient for image classification with its distinct features. In this study, three different CNNs with same architecture are trained with different training sets and combined their decisions for Bangla handwritten numeral recognition. One CNN is trained with ordinary training set prepared from handwritten scan images; and training sets for other two CNNs are prepared with fixed (positive and negative, respectively) rotational angles of original images. The proposed multiple CNN based approach is shown to outperform other existing methods while tested on a popular Bangla benchmark handwritten dataset.

Item Type:	Conference or Workshop Item (Plenary Papers)
Additional Information:	6724/51419
Uncontrolled Keywords:	multiple, convolutional, neural, network, training, Bangla handwritten, numeral, recognition
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Information and Communication Technology > Department of Computer Science Kulliyyah of Information and Communication Technology > Department of Computer Science Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology
Depositing User:	Dr. M.M. Hafizur Rahman
Date Deposited:	15 Aug 2016 15:32
Last Modified:	26 Jun 2019 14:59
URI:	http://irep.iium.edu.my/id/eprint/51419

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