Pawlak recently introduced rough set flow graphs (RSFGs) as a graphical framework for reasoning from data. Each rule is associated with three coefficients, which have been shown t...
We address the problem of object-based visual attention from a Bayesian standpoint. We contend with the issue of joint segmentation and saliency computation suitable to provide a ...
We study probabilistic inference in large, layered Bayesian networks represented as directed acyclic graphs. We show that the intractability of exact inference in such networks do...
In photometric stereo a robust method is required to deal with outliers, such as shadows and non-Lambertian reflections. In this paper we rely on a probabilistic imaging model tha...
We develop a mixture-based approach to robust density modeling and outlier detection for experimental multivariate data that includes measurement error information. Our model is d...