Improved Fuzzy C-means Clustering for Grape Leaf Disease Detection using Mathematical Morphology-Reference-Cited by-同舟云学术

Improved Fuzzy C-means Clustering for Grape Leaf Disease Detection using Mathematical Morphology

Published:2023-03-08 Issue: Volume: Page:
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Container-title:2023 International Electrical Engineering Congress (iEECON)
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Author:

Chaimanee Aphichet¹,Fu Xiaoli²,Lyu Guifen³,Angkawisittpan Niwat⁴,Chaiduangsri Nuttapon⁵,Sultornsanee Sivarit⁶

Affiliation:

1. Mahasarakham University,Faculty of Engineering,Maha Sarakham,Thailand

2. Xiamen Institute of Technology,Faculty of Architecture,Xiamen,China

3. Ningxia College of Construction,Yinchuan,China

4. Mahasarakham University,Computational Electromagnetics and Optical Systems Research Unit (CEMOS), Faculty of Engineering,Maha Sarakham,Thailand

5. Mahasarakham University,Electric Automotive and Energy Technology Research Unit (EAET), Faculty of Engineering,Maha Sarakham,Thailand

6. College of Engineering, Northeastern University,Boston,Massachusetts,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10126135/10126143/10126829.pdf?arnumber=10126829

Reference15 articles.

1. Grape leaf disease detection from color imagery using hybrid intelligent system

2. Plant disease identification from individual lesions and spots using deep learning

3. Fuzzy C-means Aalgorithm for Data Clustering with Ddistance Measurement;champathong;Joint Conference on Computer Science and Software Engineering (JCSSE),0

4. Sphaceloma Ampelinum of Grape Scab in Thailand;pienpuck;Thai Agricultural Research Journal,1993

5. Grape Cultivation;Department of Agriculture Extension,1999

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