This article presents and analyzes algorithms that systematically generate random Bayesian networks of varying difficulty levels, with respect to inference using tree clustering. ...
Current manufacturing methods for robotic-controlled assembly rely on accurate positioning to ensure task completion, often through the use of special xtures and precise calibrati...
The paper describes our first experiments on Reinforcement Learning to steer a real robot car. The applied method, Neural Fitted Q Iteration (NFQ) is purely data-driven based on ...
Martin Riedmiller, Michael Montemerlo, Hendrik Dah...
Abstract. In this paper we propose a novel approach to define task-driven regularization constraints in deformable image registration using learned deformation priors. Our method ...
Ben Glocker, Nikos Komodakis, Nassir Navab, Georgi...
-This paper describes the use of a Fuzzy Cognitive Map (FCM) to model disaster reconstruction, based on data collected from the cities of BAM and Baravat. The extended fuzzy cognit...