Coarse–fine surrogate model driven multiobjective evolutionary fuzzy clustering algorithm with dual memberships for noisy image segmentation

To improve the segmentation performance and boost evolutionary efficiency of multiobjective evolutionary clustering algorithms on noisy images, this paper proposes a coarse–fine surrogate model driven multiobjective evolutionary fuzzy clustering algorithm with dual membership functions (CFS-MOEFC)....

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Veröffentlicht in:	Applied soft computing Jg. 112; S. 107778
Hauptverfasser:	Zhao, Feng, Liu, Feifan, Li, Chaoqi, Liu, Hanqiang, Lan, Rong, Fan, Jiulun
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.11.2021
Schlagworte:	Coarse–fine surrogate model Dual fuzzy memberships Fuzzy clustering Image segmentation Multiobjective evolutionary optimization Image segmentation Coarse–fine surrogate model Fuzzy clustering Dual fuzzy memberships Multiobjective evolutionary optimization
ISSN:	1568-4946, 1872-9681
Online-Zugang:	Volltext
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