In volume visualization, users typically specify transfer functions to classify the data and assign visual attributes to each material class. Higher-dimensional classification mak...
The min-sum k-clustering problem is to partition a metric space (P, d) into k clusters C1, . . . , Ck ⊆ P such that k i=1 p,q∈Ci d(p, q) is minimized. We show the first effi...
Texture feature extraction operators, which comprise linear filtering, eventually followed by post-processing, are considered. The filters used are Laws' masks, filters deriv...
Simona E. Grigorescu, Nicolai Petkov, Peter Kruizi...
The metric 2-clustering problem is de ned as follows: given a metric (X;d), partition X into two sets S1 and S2 in order to minimize the value of X i X fu;vg Si d(u;v) In this pap...
In this paper, we define and study a novel text mining problem, which we refer to as Comparative Text Mining (CTM). Given a set of comparable text collections, the task of compara...