Development of English handwritten recognition using deep neural network

Gunawan, Teddy Surya and Mohd Noor, Ahmad Fakhrur Razi and Kartiwi, Mira (2018) Development of English handwritten recognition using deep neural network. Indonesian Journal of Electrical Engineering and Computer Science, 10 (2). pp. 562-568. ISSN 2502-4752

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Abstract

Due to the advanced in GPU and CPU, in recent years, Deep Neural Network (DNN) becomes popular to be utilized both as feature extraction and classifier. This paper aims to develop offline handwritten recognition system using DNN. First, two popular English digits and letters database, i.e. MNIST and EMNIST, were selected to provide dataset for training and testing phase of DNN. Altogether, there are 10 digits [0-9] and 52 letters [a-z, A-Z]. The proposed DNN used stacked two autoencoder layers and one softmax layer. Recognition accuracy for English digits and letters is 97.7% and 88.8%, respectively. Performance comparison with other structure of neural networks revealed that the weighted average recognition rate for patternnet, feedforwardnet, and proposed DNN were 80.3%, 68.3%, and 90.4%, respectively. It shows that our proposed system is able to recognize handwritten English digits and letters with high accuracy.

Item Type:	Article (Journal)
Additional Information:	5588/62496
Uncontrolled Keywords:	Deep neural network, EMNIST, Handwritten recognition, MNIST, Neural network
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices > TK7885 Computer engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Electrical and Computer Engineering Kulliyyah of Information and Communication Technology > Department of Information System Kulliyyah of Information and Communication Technology > Department of Information System
Depositing User:	Prof. Dr. Teddy Surya Gunawan
Date Deposited:	27 Mar 2018 16:28
Last Modified:	27 Mar 2018 16:28
URI:	http://irep.iium.edu.my/id/eprint/62496

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