Clustering is to identify densely populated subgroups in data, while correlation analysis is to find the dependency between the attributes of the data set. In this paper, we combin...
This paper presents a systematic approach based on robust statistical techniques for development of a data-driven soft sensor, which is an important component of the process analy...
Stable local feature detection and representation is a fundamental component of many image registration and object recognition algorithms. Mikolajczyk and Schmid [14] recently eva...
Subspace representations have been a popular way to model appearance in computer vision. In Jepson and Black's influential paper on EigenTracking, they were successfully appl...
Abstract. When developing statistical models of normal brain perfusion, two questions are of crucial interest: How well does an atlas describe normality and how sensitive is it at ...