Subspace clustering (also called projected clustering) addresses the problem that different sets of attributes may be relevant for different clusters in high dimensional feature sp...
In machine learning problems with tens of thousands of features and only dozens or hundreds of independent training examples, dimensionality reduction is essential for good learni...
When scientific data sets can be interpreted visually they are typically managed as pictures and consequently stored as large collections of bitmaps. Valuable information containe...
In this paper we present an indirect volume visualization method, based on the deformable surface model, which is a three dimensional extension of the snake segmentation method. I...
The faithful detection of the motion and of the distance of the objects in the visual scene is a desirable feature of any artificial vision system designed to operate in unknown e...