The representation model that considers an image as a sparse linear combination of few atoms of a predefined or learned dictionary has received considerable attention in recent ye...
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...
We present a multiclass classification system for gray value images through boosting. The feature selection is done using the LPBoost algorithm which selects suitable features of a...
Martin Antenreiter, Christian Savu-Krohn, Peter Au...
We present a novel stereo vision modeling framework that generates approximate, yet physically-plausible representations of objects rather than creating accurate models that are c...
Krishnanand N. Kaipa, Josh C. Bongard, Andrew N. M...
This paper presents a spoken dialogue framework that helps users in making decisions. Users often do not have a definite goal or criteria for selecting from a list of alternatives...