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EUROGRAPHICS
2010
Eurographics
14 years 1 months ago
Fast High-Dimensional Filtering Using the Permutohedral Lattice
Many useful algorithms for processing images and geometry fall under the general framework of high-dimensional Gaussian filtering. This family of algorithms includes bilateral ...
Andrew Adams, Jongmin Baek, Myers Abraham Davis
VISSYM
2004
13 years 6 months ago
Volume Visualization and Visual Queries for Large High-Dimensional Datasets
We propose a flexible approach for the visualization of large, high-dimensional datasets. The raw, highdimensional data is mapped into an abstract 3D distance space using the Fast...
Guido Reina, Thomas Ertl
ICML
2003
IEEE
14 years 5 months ago
Feature Selection for High-Dimensional Data: A Fast Correlation-Based Filter Solution
Feature selection, as a preprocessing step to machine learning, has been effective in reducing dimensionality, removing irrelevant data, increasing learning accuracy, and improvin...
Lei Yu, Huan Liu
ICIP
2007
IEEE
13 years 11 months ago
H2O: Reversible Hexagonal-Orthogonal Grid Conversion by 1-D Filtering
In this work, we propose a new grid conversion algorithm between the hexagonal lattice and the orthogonal (a.k.a. Cartesian) lattice. The conversion process, named H2O, is easy to...
Laurent Condat, Brigitte Forster-Heinlein, Dimitri...
TIP
2008
90views more  TIP 2008»
13 years 4 months ago
Reversible, Fast, and High-Quality Grid Conversions
Abstract--A new grid conversion method is proposed to resample between two 2-D periodic lattices with the same sampling density. The main feature of our approach is the symmetric r...
Laurent Condat, Dimitri Van De Ville, Brigitte For...