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Normalized sampling for color clustering in medical diagnosis | IEEE Conference Publication | IEEE Xplore
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Normalized sampling for color clustering in medical diagnosis


Abstract:

The classical approach of using minimum cut criterion for clustering is often ineffective due to the existence of outliers in the data. This paper presents a novel normal...Show More

Abstract:

The classical approach of using minimum cut criterion for clustering is often ineffective due to the existence of outliers in the data. This paper presents a novel normalized graph sampling algorithm for clustering that improves the solution of clustering via the incorporation of a priori constraint in a stochastic graph sampling procedure. The quality of the proposed algorithm is empirically evaluated on two synthetic datasets and a color medical image database.
Date of Conference: 11-15 August 2002
Date Added to IEEE Xplore: 10 December 2002
Print ISBN:0-7695-1695-X
Print ISSN: 1051-4651
Conference Location: Quebec City, QC, Canada

References

References is not available for this document.