This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
In multi-hop networks, packet schedulers at downstream nodes have an opportunity to make up for excessive latencies due to congestion at upstream nodes. Similarly, when packets inc...
In this paper, we propose a robust incremental learning framework for accurate skin region segmentation in real-life images. The proposed framework is able to automatically learn ...
—Despite active research and significant progress in the last 30 years, eye detection and tracking remains challenging due to the individuality of eyes, occlusion, variability in...
Business applications are facing an increasing demand for being delivered as on-demand services. Service Level Agreements (SLAs) are a common way for specifying the exact condition...
Wolfgang Theilmann, Ulrich Winkler, Jens Happe, Il...