In recent years realistic input models for geometric algorithms have been studied. The most important models introduced are fatness, low density, unclutteredness, and small simple...
Mark de Berg, Haggai David, Matthew J. Katz, Mark ...
Astronomy increasingly faces the issue of massive datasets. For instance, the Sloan Digital Sky Survey (SDSS) has so far generated tens of millions of images of distant galaxies, ...
Brigham Anderson, Andrew W. Moore, Andrew Connolly...
Commercial aerial imagery websites, such as Google Maps, MapQuest, Microsoft Virtual Earth, and Yahoo! Maps, provide high- seamless orthographic imagery for many populated areas, ...
Peter Pesti, Jeremy Elson, Jon Howell, Drew Steedl...
Background: The expansion of automatic imaging technologies has created a need to be able to efficiently compare and review large sets of image data. To enable comparisons of imag...
Dimensionality reduction is a much-studied task in machine learning in which high-dimensional data is mapped, possibly via a non-linear transformation, onto a low-dimensional mani...