We consider object recognition as the process of attaching meaningful labels to specific regions of an image, and propose a model that learns spatial relationships between objects....
We propose an active vision system for object acquisition. The core of our approach is a reinforcement learning module which learns a strategy to scan an object. The agent moves a...
Gabriele Peters, Claus-Peter Alberts, Markus Bries...
ys when planning meant searching for a sequence of abstract actions that satisfied some symbolic predicate. Robots can now learn their own representations through statistical infe...
Knowledge transfer between expert and novice agents is a challenging problem given that the knowledge representation and learning algorithms used by the novice learner can be fund...
Abstract. This work proposes a family of language-independent semantic kernel functions defined for individuals in an ontology. This allows exploiting wellfounded kernel methods fo...