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EUROGRAPHICS
2010
Eurographics
14 years 4 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 8 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 8 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
14 years 1 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 7 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...