This paper describes a computational learning model inspired by the technology of optical thin-film multilayers from the field of optics. With the thicknesses of thin-film layers ...
Bayesian learning in undirected graphical models--computing posterior distributions over parameters and predictive quantities-is exceptionally difficult. We conjecture that for ge...
A new probabilistic background model based on a Hidden Markov Model is presented. The hidden states of the model enable discrimination between foreground, background and shadow. Th...
The research field of transportation demand forecasting has started to focus on disaggregate travel behavior and micro-simulation models. To create data infrastructure, disaggrega...
Ali Frihida, Danielle J. Marceau, Marius Thé...
In this paper, we propose a probabilistic model for web image mining, which is based on concept-sensitive salient regions without human intervene. Our goal is to achieve a middle-...