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ICPR
2006
IEEE
14 years 8 months ago
Adaptive Feature Integration for Segmentation of 3D Data by Unsupervised Density Estimation
In this paper, a novel unsupervised approach for the segmentation of unorganized 3D points sets is proposed. The method derives by the mean shift clustering paradigm devoted to se...
Marco Cristani, Umberto Castellani, Vittorio Murin...
ISBI
2004
IEEE
14 years 8 months ago
Microarray Gene Expression Data Analysis
Image analysis is a crucial step in processing microarray data generated by gene expression studies, which have been used extensively in understanding the molecular mechanisms of ...
Yuhua Ding, Jacqueline Fairley, George J. Vachtsev...
ICIP
2005
IEEE
14 years 9 months ago
Fuzzy image segmentation of generic shaped clusters
Abstract The segmentation performance of any clustering algorithm is very sensitive to the features in an image, which ultimately restricts their generalization capability. This li...
Mohammed Ameer Ali, Gour C. Karmakar, Laurence S. ...
RSFDGRC
2005
Springer
100views Data Mining» more  RSFDGRC 2005»
14 years 26 days ago
A Hybrid Approach to MR Imaging Segmentation Using Unsupervised Clustering and Approximate Reducts
Abstract. We introduce a hybrid approach to magnetic resonance image segmentation using unsupervised clustering and the rules derived from approximate decision reducts. We utilize ...
Sebastian Widz, Kenneth Revett, Dominik Slezak
ICIP
2010
IEEE
13 years 5 months ago
Edge-adaptive image segmentation based on seam processing and K-Means clustering
A new image segmentation method is proposed to combine the edge information with the feature-space method, K-Means clustering. A procedure called seam processing, which is computa...
Tse-Wei Chen, Hsiao-Hang Su, Yi-Ling Chen, Shao-Yi...