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PR
2006
84views more  PR 2006»
13 years 4 months ago
Geometric visualization of clusters obtained from fuzzy clustering algorithms
Fuzzy-clustering methods, such as fuzzy k-means and Expectation Maximization, allow an object to be assigned to multiple clusters with different degrees of membership. However, th...
Luis Rueda, Yuanquan Zhang
SCCC
2005
IEEE
13 years 10 months ago
A geometric framework to visualize fuzzy-clustered data
— Fuzzy clustering methods have been widely used in many applications. These methods, including fuzzy k-means and Expectation Maximization, allow an object to be assigned to mult...
Yuanquan Zhang, Luis Rueda
SEDE
2008
13 years 6 months ago
Improving Fuzzy Algorithms for Automatic Magnetic Resonance Image Segmentation
: In this paper, we present reliable algorithms for fuzzy k-means and C-means that could improve MRI segmentation. Since the k-means or FCM method aims to minimize the sum of squar...
Ennumeri A. Zanaty, Sultan Aljahdali, Narayan C. D...
WILF
2009
Springer
791views Fuzzy Logic» more  WILF 2009»
14 years 3 months ago
Fuzzy C-Means Inspired Free Form Deformation Technique for Registration
This paper presents a novel method aimed to free form deformation function approximation for purpose of image registration. The method is currently feature-based. The algorithm i...
Edoardo Ardizzone, Orazio Gambino, Roberto Gallea,...
IJIT
2004
13 years 6 months ago
On the Noise Distance in Robust Fuzzy C-Means
In the last decades, a number of robust fuzzy clustering algorithms have been proposed to partition data sets affected by noise and outliers. Robust fuzzy C-means (robust-FCM) is c...
Mario G. C. A. Cimino, Graziano Frosini, Beatrice ...