This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
Reducing redundancy in search has been a major concern for automated deduction. Subgoal-reduction strategies, such as those based on model elimination and implemented in Prolog te...
—Deformable models have recently been proposed for many pattern recognition applications due to their ability to handle large shape variations.These proposed approaches represent...
—This paper describes a probabilistic technique for the coupled reconstruction and restoration of underwater acoustic images. The technique is founded on the physics of the image...
Vittorio Murino, Andrea Trucco, Carlo S. Regazzoni
Many interesting analyses for constraint logic-based languages are aimed at the detection of monotonic properties, that is to say, properties that are preserved as the computation...