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. ...
We present a novel algorithm for agglomerative hierarchical clustering based on evaluating marginal likelihoods of a probabilistic model. This algorithm has several advantages ove...
The RKLT is a lossless approximation to the KLT, and has been recently employed for progressive lossy-to-lossless coding of hyperspectral images. Both yield very good coding perfo...
Ontologies represent data relationships as hierarchies of possibly overlapping classes. Ontologies are closely related to clustering hierarchies, and in this article we explore th...
Jinze Liu, Qi Zhang, Wei Wang 0010, Leonard McMill...
Abstract. We present the first (to our knowledge) approximation algorithm for tensor clustering—a powerful generalization to basic 1D clustering. Tensors are increasingly common...