This paper develops a weakly supervised algorithm that learns to segment rigid multi-colored objects from a set of training images and key points. The approach uses congealing to ...
Douglas Moore, John Stevens, Scott Lundberg, Bruce...
Abstract. We present a novel approach to representing uncertain information in ontologies based on design patterns. We provide a brief description of our approach, present its use ...
Multiplysectioned Bayesian networks provide a probabilistic framework for reasoning about uncertain domains in cooperative multiagent systems. Several advances have been made in r...
Abstract. The paper proposes a simulation-based method for validating analog and mixed-signal circuits, using the hybrid systems methodology. This method builds upon RRT (Rapidly-e...
Proper reuse of learning objects depends both on the amount and quality of attached semantic metadata such as “learning objective”', “related concept”, etc. Manually ...
Paramjeet Singh Saini, Marco Ronchetti, Diego Sona