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...
A multiresolution data decomposition offers a fundamental framework supporting compression, progressive transmission, and level-of-detail (LOD) control for large two or three dime...
Wenli Cai, Georgios Sakas, Roberto Grosso, Thomas ...
— The engineering of complex production automation systems involves experts from several backgrounds, such as mechanical, electrical, and software engineering. The production aut...
Thomas Moser, Stefan Biffl, Wikan Danar Sunindyo, ...
The conflict between resource consumption and query performance in the data mining context often has no satisfactory solution. This not only stands in sharp contrast to the need of...
Matthias Gimbel, Michael Klein, Peter C. Lockemann
In this paper, a new graph data structure for 2-D shape representation is proposed. The new structure is called a concavity graph, and is an evolution from the already known "...