This paper introduces design principles for modular Bayesian fusion systems which can (i) cope with large quantities of heterogeneous information and (ii) can adapt to changing co...
Gregor Pavlin, Patrick de Oude, Marinus Maris, Jan...
Matrix factorization is a fundamental technique in machine learning that is applicable to collaborative filtering, information retrieval and many other areas. In collaborative fil...
In the present study, an efficient strategy for retrieving texture images from large texture databases is introduced and studied within a distributional-statistical framework. Our...
Vasileios K. Pothos, Christos Theoharatos, George ...
In this work we consider a mobile robot with a laser range finder. Our goal is to find the best set of lines from the sequence of points given by a laser scan. We propose a probabi...
In this paper, a Bayesian LBP operator is proposed. This operator is formulated in a novel Filtering, Labeling and Statistic (FLS) framework for texture descriptors. In the framew...