Abstract-- Data uncertainty is common in real-world applications due to various causes, including imprecise measurement, network latency, outdated sources and sampling errors. Thes...
Traditional decision tree classifiers work with data whose values are known and precise. We extend such classifiers to handle data with uncertain information, which originates from...
Smith Tsang, Ben Kao, Kevin Y. Yip, Wai-Shing Ho, ...
Abstract-- In sensor environments and moving robot applications, the position of an object is often known imprecisely because of measurement error and/or movement of the object. In...
This paper proposes a colorimetric characterization method using the color correlation between the colorants in a hi-fi printer. While several colorant combinations can be used to...
In-Su Jang, Chang-Hwan Son, Tae-Yong Park, Kyung-W...
This paper proposes a new method for the selection of sets of omnidirectional views, which contribute together to the efficient representation of a 3D scene. When the 3D surface i...