A game-theoretic approach for learning optimal parameter values for probabilistic rough set regions is presented. The parameters can be used to define approximation regions in a p...
We present a new method for carrying out state estimation in multiagent settings that are characterized by continuous or large discrete state spaces. State estimation in multiagen...
Scale space interest points capture important photometric and deep structure information of an image. The information content of such points can be made explicit using image recons...
Frans Kanters, Trip Denton, Ali Shokoufandeh, Luc ...
We study the evolution of T-spline level sets (i.e, implicitly defined T-spline curves and surfaces). The use of T-splines leads to a sparse representation of the geometry and al...
Teachers working in robotics classes face a major problem: how to keep track on individual students’ or even small groups’ progress in a class of 30-40 students. A multi-agent...
Ilkka Jormanainen, Chiara Moroni, Yuejun Zhang, Ki...