A Type-2 Fuzzy Clustering and Quantum Optimization Approach for Crops Image Segmentation

Automatic detection of crop yield ripeness is a tedious task because of the presence of various intensities of color in crops. One of the solutions to this problem is the monitoring of those crops by performing segmentation operations. This operation can help to distinguish the ripe and non-ripe reg...

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Veröffentlicht in:	International journal of fuzzy systems Jg. 23; H. 3; S. 615 - 629
Hauptverfasser:	Huang, Yo-Ping, Singh, Pritpal, Kuo, Wen-Lin, Chu, Hung-Chi
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2021 Springer Nature B.V
Schlagworte:	Algorithms Artificial Intelligence Cluster analysis Clustering Color imagery Computational Intelligence Computer vision Crop yield Engineering Fuzzy sets Image segmentation Management Science Memberships Methods Operations Research Optimization Pattern recognition Researchers Set theory Support vector machines Vector quantization Modified quantum optimization algorithm (MQOA) Image segmentation means clustering Fuzzy set
ISSN:	1562-2479, 2199-3211
Online-Zugang:	Volltext
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