This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
Abstract. We present a framework for combining automated and interactive visual analysis techniques for use on high-resolution biomechanical data. Analyzing the complex 3D motion o...
Scott Spurlock, Remco Chang, Xiaoyu Wang, George A...
How to achieve shared meaning is a significant issue when more than one intelligent agent is involved in the same domain. We define the task of concept convergence, by which intell...
Due to the lack of explicit spatial consideration, existing
epitome model may fail for image recognition and target detection,
which directly motivates us to propose the so-calle...
Xinqi Chu, Shuicheng Yan, Liyuan Li, Kap Luk Chan,...
We present a machine learning framework that automatically generates a model set of landmarks for some class of registered 3D objects: here we use human faces. The aim is to repla...