Feature extraction for neural-fuzzy inference system

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-CHA...

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Main Authors: Quek, Chai, See Ng, Goek, Abdul Rahman, Abdul Wahab
Format: Proceeding Paper
Language:English
Published: 2003
Subjects:
Online Access:http://irep.iium.edu.my/38845/
http://irep.iium.edu.my/38845/1/Feature_Extraction_for_Neural-Fuzzy_Inference_System.pdf
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author Quek, Chai
See Ng, Goek
Abdul Rahman, Abdul Wahab
author_facet Quek, Chai
See Ng, Goek
Abdul Rahman, Abdul Wahab
author_sort Quek, Chai
building IIUM Repository
collection Online Access
description 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.
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format Proceeding Paper
id iium-38845
institution International Islamic University Malaysia
institution_category Local University
language English
last_indexed 2025-11-14T15:53:24Z
publishDate 2003
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repository_type Digital Repository
spelling iium-388452020-12-16T15:45:24Z http://irep.iium.edu.my/38845/ Feature extraction for neural-fuzzy inference system Quek, Chai See Ng, Goek Abdul Rahman, Abdul Wahab T Technology (General) 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. 2003-07 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/38845/1/Feature_Extraction_for_Neural-Fuzzy_Inference_System.pdf 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. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1223702
spellingShingle T Technology (General)
Quek, Chai
See Ng, Goek
Abdul Rahman, Abdul Wahab
Feature extraction for neural-fuzzy inference system
title Feature extraction for neural-fuzzy inference system
title_full Feature extraction for neural-fuzzy inference system
title_fullStr Feature extraction for neural-fuzzy inference system
title_full_unstemmed Feature extraction for neural-fuzzy inference system
title_short Feature extraction for neural-fuzzy inference system
title_sort feature extraction for neural-fuzzy inference system
topic T Technology (General)
url http://irep.iium.edu.my/38845/
http://irep.iium.edu.my/38845/
http://irep.iium.edu.my/38845/1/Feature_Extraction_for_Neural-Fuzzy_Inference_System.pdf