Generalization, in its most basic form, is an artificial neural network's (ANN's) ability to automatically classify data that were not seen during training. This paper p...
This paper addresses the problem of compensating for lateral chromatic aberration in digital images through colour plane realignment. Two main contributions are made: the derivati...
We present an efficient method for volume rendering by raycasting on the CPU. We employ coherent packet traversal of an implicit bounding volume hierarchy, heuristically pruned u...
Aaron Knoll, Sebastian Thelen, Ingo Wald, Charles ...
We introduce variant types and a pattern matching operation to synchronous dataflow languages. These languages are used in the design of reactive systems. As these systems grow in...
Abstract. In this paper we elaborate on the challenges of learning manifolds that have many relevant clusters, and where the clusters can have widely varying statistics. We call su...