We present a computational framework designed to provide adaptive support aimed at triggering learning from problem-solving activities in the presence of worked-out examples. The k...
Abstract. The importance of spatial configuration information for object class recognition is widely recognized. Single isolated local appearance codes are often ambiguous. On the...
There has been much recent work on measuring image statistics and on learning probability distributions on images. We observe that the mapping from images to statistics is many-to...
We present an approach for online learning of discriminative appearance models for robust multi-target tracking in a crowded scene from a single camera. Although much progress has...
We present a novel approach to machine learning, called ABML (argumentation based ML). This approach combines machine learning from examples with concepts from the field of argum...