This article presents and analyzes algorithms that systematically generate random Bayesian networks of varying difficulty levels, with respect to inference using tree clustering. ...
We present a novel global stereo model that makes use of constraints from points with known depths, i.e., the Ground Control Points (GCPs) as referred to in stereo literature. Our...
Graph transduction methods label input data by learning a classification function that is regularized to exhibit smoothness along a graph over labeled and unlabeled samples. In pr...
Tumor segmentation in PET and CT images is notoriously challenging due to the low spatial resolution in PET and low contrast in CT images. In this paper, we proposed a general fram...
Dongfeng Han, John E. Bayouth, Qi Song, Aakant Tau...
We propose a method to identify and localize object
classes in images. Instead of operating at the pixel level,
we advocate the use of superpixels as the basic unit of a
class s...