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SEDE
2008
13 years 8 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...
JDCTA
2010
228views more  JDCTA 2010»
13 years 2 months ago
Research and Progress of Cluster Algorithms based on Granular Computing
Granular Computing (GrC), a knowledge-oriented computing which covers the theory of fuzzy information granularity, rough set theory, the theory of quotient space and interval comp...
Shifei Ding, Li Xu, Hong Zhu, Liwen Zhang
BMVC
1998
13 years 8 months ago
A Method for Dynamic Clustering of Data
This paper describes a method for the segmentation of dynamic data. It extends well known algorithms developed in the context of static clustering (e.g., the c-means algorithm, Ko...
Arnaldo J. Abrantes, Jorge S. Marques
CIT
2007
Springer
14 years 1 months ago
Performance Assessment of Some Clustering Algorithms Based on a Fuzzy Granulation-Degranulation Criterion
In this paper a fuzzy quantization dequantization criterion is used to propose an evaluation technique to determine the appropriate clustering algorithm suitable for a particular ...
Sriparna Saha, Sanghamitra Bandyopadhyay
FSKD
2005
Springer
141views Fuzzy Logic» more  FSKD 2005»
14 years 28 days ago
Spatial Homogeneity-Based Fuzzy c-Means Algorithm for Image Segmentation
Abstract. A fuzzy c-means algorithm incorporating the notion of dominant colors and spatial homogeneity is proposed for the color clustering problem. The proposed algorithm extract...
Bo-Yeong Kang, Dae-Won Kim, Qing Li