Dental Fluorosis Segmentation Using Enhanced Quantum-Inspired Fuzzy Clustering Algorithm-Reference-Cited by-同舟云学术

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Dental Fluorosis Segmentation Using Enhanced Quantum-Inspired Fuzzy Clustering Algorithm

Published:2022-07-05 Issue: Volume: Page:
ISSN:
Container-title:2022 37th International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC)
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Author:

Petaitiemthong Natchapon¹,Auephanwiriyakul Sansanee²,Theera-Umpon Nipon³,Kongpun Chatpat⁴

Affiliation:

1. Chiang Mai University,Faculty of Engineering Graduate School,Computer Engineering Department,Chiang Mai,Thailand

2. Biomedical Engineering Institute, Chiang Mai University,Faculty of Engineering,Computer Engineering Department,Chiang Mai,Thailand

3. Biomedical Engineering Institute, Chiang Mai University,Faculty of Engineering,Electrical Engineering Department,Chiang Mai,Thailand

4. Intercountry Centre for Oral Health,Ministry of Public Health,Department of Health,Thailand

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9894733/9894851/09894942.pdf?arnumber=9894942

Reference13 articles.

1. Pattern Recognition with Fuzzy Objective Function Algorithms

2. Enhanced cluster validity index for the evaluation of optimal number of clusters for Fuzzy C-Means algorithm

3. Dental fluorosis classification using multi-prototypes from fuzzy C-means clustering

4. Nearest neighbor pattern classification

5. Dental fluorosis in populations from Chiang Mai, Thailand with different fluoride exposures – Paper 1: assessing fluorosis risk, predictors of fluorosis and the potential role of food preparation

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