Application of EFUNN for the classification of handwritten digits

• Main Authors: Geok, See Ng, Murali, T., Shi, Dingding, Abdul Rahman, Abdul Wahab
• Format: Article
• Language: English
• Published: International Journal of Computers, Systems and Signals 2004
• Subjects: T Technology (General)
• Online Access: http://irep.iium.edu.my/38192/1/Application_of_EFUNN_for_the_Classification_of_Handwritten_Digits.pdf; http://irep.iium.edu.my/38192/; http://www.informatik.uni-trier.de/~ley/db/journals/ijcss/ijcss5.html

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.