Application of EFUNN for the classification of handwritten digits

Geok, See Ng and Murali, T. and Shi, Dingding and Abdul Rahman, Abdul Wahab (2004) Application of EFUNN for the classification of handwritten digits. International Journal of Computers, Systems and Signals, 5 (2). pp. 27-35.

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Abstract

Handwritten digits classification has many useful applications. This has prompted decades of research into algorithms to produce an effective system of classifying handwritten images into text. Image processing and feature extraction play a large role in this process. An intelligent system is one, which is taught, and one, which uses this learning for classification effectively. The neuro-fuzzy model of Evolving Fuzzy Neural Network (EFuNN) is used for this purpose. This paper aims to analyse and obtain the optimal number of features that will produce the most effective classification using EFuNN.

Item Type:	Article (Journal)
Additional Information:	6145/38192
Uncontrolled Keywords:	Neural networks, Evolving computation, Handwritten digit recognition, Image processing.
Subjects:	T Technology > T Technology (General)
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
Depositing User:	Ahmad Nazreen Mohd Shamsuri (PT)
Date Deposited:	12 Sep 2014 09:34
Last Modified:	12 Sep 2014 09:34
URI:	http://irep.iium.edu.my/id/eprint/38192

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