We describe methods for displaying complex, texturemapped environments with four or more spatial dimensions that allow for real-time interaction. At any one moment in time, a thre...
Michael D'Zmura, Philippe Colantoni, Gregory Seyra...
Feature space analysis is the main module in many computer vision tasks. The most popular technique, k-means clustering, however, has two inherent limitations: the clusters are co...
— Today's innovations in the automotive sector are, to a great extent, based on electronics. The increasing integration complexity and stringent cost reduction goals turn E/...
In this paper, we present a new capacitance extraction method named Dimension Reduction Technique (DRT) for 3D VLSI interconnects. The DRT converts a complex 3D problem into a ser...
Wei Hong II, Weikai Sun, Zhenhai Zhu, Hao Ji, Ben ...
Manifold learning is an effective methodology for extracting nonlinear structures from high-dimensional data with many applications in image analysis, computer vision, text data a...