We propose a fully Bayesian methodology for generalized kernel mixed models (GKMMs), which are extensions of generalized linear mixed models in the feature space induced by a repr...
This paper presents a Markov Random Field (MRF)-based approach for depth map super-resolution and enhancement. Given a low-resolution or moderate quality depth map, we study the p...
We address several challenges for applying statistical dialog managers based on Partially Observable Markov Models to real world problems: to deal with large numbers of concepts, ...
Sebastian Varges, Giuseppe Riccardi, Silvia Quarte...
In this paper we study various chain codes, which are representations of binary image contours, in terms of their ability to compress in the best way the contour information using...