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Pixel-level labelling tasks, such as semantic segmentation, play a central role in image understanding. Recent approaches have… Expand This paper addresses semantic image segmentation by incorporating rich information into Markov Random Field (MRF), including high… Expand In this paper we study the problem of object detection for RGB-D images using semantically rich image and depth features. We… Expand We propose a new family of description logics (DLs), called DL-Lite, specifically tailored to capture basic ontology languages… Expand Abstract
This paper details a new approach for learning a discriminative model of object classes, incorporating texture, layout… Expand We describe a slightly subexponential time algorithm for learning parity functions in the presence of random classification noise… Expand We develop a new schema for unstructured data. Traditional schemas resemble the type systems of programming languages. For… Expand Abstract This paper extends network-based methods of constraint satisfaction to include continuous variables, thus providing a… Expand An algorithm is described which is capable of solving certain word problems: i.e. of deciding whether or not two words composed… Expand This paper is an attempt at developing a theory of algebraic systems that would correspond in a natural fashion to the No-valued… Expand