We have proposed a novel model-based compression technique for nonstationary landmark shape data extracted from video sequences. The main goal is to develop a technique for the co...
Markov random fields (MRFs) are popular and generic probabilistic models of prior knowledge in low-level vision. Yet their generative properties are rarely examined, while applica...
This paper presents a method for estimating uncertainty in MRI-based brain region delineations provided by fully-automated segmentation methods. In large data sets, the uncertainty...
Karl R. Beutner, Gautam Prasad, Evan Fletcher, Cha...
Classifying pictures into one of several semantic categories is a classical image understanding problem. In this paper, we present a stratified approach to both binary (outdoor-in...
Astronomy increasingly faces the issue of massive datasets. For instance, the Sloan Digital Sky Survey (SDSS) has so far generated tens of millions of images of distant galaxies, ...
Brigham Anderson, Andrew W. Moore, Andrew Connolly...