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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Vydané v:	Engineering applications of artificial intelligence Ročník 163; s. 113045
Hlavní autori:	Chong, Qianpeng, Wen, Jiakun, Wan, Qianhui, Zeng, Wenyi, Yin, Qian, Cheng, Dong
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 01.01.2026
Predmet:	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
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