Enhanced independent component analysis and fuzzy C-mean clustering based on novel bat algorithm for noisy image segmentation

Fuzzy c-means clustering is widely recognized as one of the most effective methods for image segmentation and achieving accurate classification. However, this method has two significant drawbacks: its sensitivity to noise and its convergence to local minimum clusters’ centroids. In this paper, we pr...

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Vydáno v:	Engineering Research Express Ročník 5; číslo 4; s. 45041 - 45058
Hlavní autoři:	Chetih, Nabil, Thelaidjia, Tawfik, Boudani, Fatma Zohra
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	IOP Publishing 01.12.2023
Témata:	enhanced independent component analysis fuzzy c-means clustering image segmentation noisy images novel bat algorithm regions of interest
ISSN:	2631-8695, 2631-8695
On-line přístup:	Získat plný text
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