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Selecting texture discriminative descriptors of capsule endpscopy images
2009
2009 Proceedings of 6th International Symposium on Image and Signal Processing and Analysis
In supervised data classification one of the problems is to reduce dimensionality of feature vectors. It is important to find such features which have high ability for discrimination of diverse classes and to get rid of features which are useless for such discrimination. In this paper we propose a new method for feature subset selection utilizing a convex hull (or convex polytope). The method searches for feature space subspaces in which vectors of one class cluster and they are surrounded by
doi:10.1109/ispa.2009.5297634
fatcat:ixcp7n47ujf7tavu2rv5mjnx3y