Traditional approaches to combining classifiers attempt to improve classification accuracy at the cost of increased processing. They may be viewed as providing an accuracy-speed tr...
Kumar Chellapilla, Michael Shilman, Patrice Simard
In this paper we present an efficient and general approach to computing and integrating 3D distance fields directly from multiple range images. We compute normal and confidence va...
Abstract. We present a fast and accurate tool for semiautomatic segmentation of volumetric medical images based on the live wire algorithm, shape-based interpolation and a new opti...
Andrea Schenk, Guido P. M. Prause, Heinz-Otto Peit...
Compositional Q-Learning (CQ-L) (Singh 1992) is a modular approach to learning to performcomposite tasks made up of several elemental tasks by reinforcement learning. Skills acqui...
Since Bayesian network (BN) was introduced in the field of artificial intelligence in 1980s, a number of inference algorithms have been developed for probabilistic reasoning. Ho...