A small-object segmentation algorithm for intercluster imbalance based on histogram- and stickiness-aware boosting

Traditional fuzzy C-means (FCM) clustering and its variants, as important unsupervised image segmentation methods, have average performance, usually perform poorly in the face of unbalanced datasets, and are sensitive to the initial position. Therefore, in this paper, we propose a small-object segme...

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Veröffentlicht in:	Engineering applications of artificial intelligence Jg. 163; S. 113045
Hauptverfasser:	Chong, Qianpeng, Wen, Jiakun, Wan, Qianhui, Zeng, Wenyi, Yin, Qian, Cheng, Dong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.01.2026
Schlagworte:	Fuzzy C-means algorithm Image segmentation Small-object detection Unequal clusters Image segmentation Unequal clusters Fuzzy C-means algorithm Small-object detection
ISSN:	0952-1976
Online-Zugang:	Volltext
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