In this paper, a spatially constrained mixture model for the segmentation of MR brain images is presented. The novelty of this work is a new, edge preserving, smoothness prior whic...
Giorgos Sfikas, Christophoros Nikou, Nikolas P. ...
Supervised topic models utilize document's side information for discovering predictive low dimensional representations of documents; and existing models apply likelihoodbased...
Abstract-- Associative classification is a new classification approach integrating association mining and classification. It becomes a significant tool for knowledge discovery and ...
In this paper, we propose a general two-dimensional hidden Markov model (2D-HMM), where dependency of the state transition probability on any state is allowed as long as causality...
This paper addresses the problem of classifying Chinese unknown words into fine-grained semantic categories defined in a Chinese thesaurus. We describe three novel knowledge-based...