In this paper, we present a patch-based variational Bayesian framework of image processing using the language of factor graphs (FGs). The variable and factor nodes of FGs represen...
In this project, we are developing new text processing tools that help people perform advanced analysis of large collections of text commentary. This problem is increasingly faced...
Stuart W. Shulman, Eduard H. Hovy, Jamie Callan, S...
We present parallel algorithms for processing, extracting and rendering adaptively sampled regular terrain datasets represented as a multiresolution model defined by a super-squa...
Some instructions have more impact on processor performance than others. Identification of these critical instructions can be used to modify and improve instruction processing. Pr...
Samantika Subramaniam, Anne Bracy, Hong Wang 0003,...
This paper presents a novel motion segmentation algorithm on the basis of mixture of Dirichlet process (MDP) models, a kind of nonparametric Bayesian framework. In contrast to pre...