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We propose using a data preprocessing technique to automate the selection and labeling of points of interest from unlabeled data for the purpose of semisupervised clustering. The preprocessing approach, called MembershipMap, strives to extract the underlying sub-concepts of each attribute, and uses the orthogonal union of these sub-concepts to define a new, semantically richer, space. Using the MembershipMap,...
This paper proposed an algorithm using Bayesian on-line learning for object based video image segmentation. First the strengths of image pixel's spatial location, color and motion segments are weighted and then unified in one framework for image clustering and segmentation. Here, the appropriate modeling of probability distribution functions (PDF) of each feature cluster is obtained through Gaussian...
A multi-stage hierarchical clustering technique, which is an unsupervised technique, has been proposed in this paper for classifying the hyperspectral data. The multistage algorithm consists of two stages. The "local" segmentor of the first stage performs region-growing segmentation by employing the hierarchical clustering procedure with the restriction that pixels in a cluster must be spatially...
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