Model learning and tracking are two important topics in computer vision. While there are many applications where one of them is used to support the other, there are currently only...
We present a novel approach to weakly supervised semantic class learning from the web, using a single powerful hyponym pattern combined with graph structures, which capture two pr...
We propose a new evolutionary method of extracting user preferences from examples shown to an automatic graph layout system. Using stochastic methods such as simulated annealing a...
Abstract. In the stream of research that aims to speed up practical planners, we propose a new approach to task planning based on Probabilistic Roadmap Methods (PRM). Our contribut...
We build a generic methodology based on learning and reasoning to detect specific attitudes of human agents and patterns of their interactions. Human attitudes are determined in te...
Boris Galitsky, Boris Kovalerchuk, Sergei O. Kuzne...