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Influence of the Type of Distance Measure on Sensitivity of Neuro-Fuzzy Clustering for Multidimensional Data
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UDC: 004.93
Publication Language: Russian
Stuc. intelekt. 2012; 17(4):535-545
Abstract: This article deals with the description of the hybrid fuzzy clustering algorithm mdsFCM, which is used non-Euclidian distances based on calculation the covariance matrix. This algorithm has the greater level of sensitivity while processing multidimensional data. The experimental results of the application of the proposed algorithm for low-contrast medical color images clustering are shown.
Keywords: multidimensional images, neuro-fuzzy clustering, distance measures, segmentation, non-Euclidean metrics
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