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Feature extraction for neural-fuzzy inference system

Quek, Chai and See Ng, Goek and Abdul Rahman, Abdul Wahab (2003) Feature extraction for neural-fuzzy inference system. In: International Joint Conference on Neural Network (IJCNN 2003), 20-24 July 2003 , Portland, Oregon.

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Abstract

Currently, not many attempts are made to use neural-fuzzy inference system for recognizing primitive features of an input image. The objective of this paper is to propose a method of feature extraction so as the features obtained can be trained in a novel neural-fuzzy inference system called POP-CHAR. Common features of digit characters are extracted and converted into vectors. The neural-fuzzy inference system can be trained from the primitive feature vectors and produce good results. Once the fuzzy neural network is trained, it can be used to recognize digits.

Item Type: Conference or Workshop Item (Full Paper)
Additional Information: 6145/38845
Uncontrolled Keywords: neural-fuzzy inference system
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: Prof Abdul Wahab Abdul Rahman
Date Deposited: 21 Oct 2014 15:51
Last Modified: 21 Oct 2014 15:51
URI: http://irep.iium.edu.my/id/eprint/38845

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