The design of robust classifiers, which can contend with the noisy and outlier ridden datasets typical of computer vision, is studied. It is argued that such robustness requires l...
The driving force of our current research is the development of medical training systems using augmented reality techniques. To provide multimodal feedback for the simulation, hapt...
Heterogeneous and dirty data is abundant. It is stored under different, often opaque schemata, it represents identical real-world objects multiple times, causing duplicates, and ...
Alexander Bilke, Jens Bleiholder, Christoph Bö...
Bottom-up, fully unsupervised segmentation remains a daunting challenge for computer vision. In the cosegmentation context, on the other hand, the availability of multiple images ...
Objective: To introduce the availability of grant-to-article linkage data associated with NIH grants and to perform a high-level analysis of the publication outputs and impacts as...