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ICPR
2006
IEEE
14 years 8 months ago
Invariant Features for 3D-Data based on Group Integration using Directional Information and Spherical Harmonic Expansion
Due to the increasing amount of 3D data for various applications there is a growing need for classification and search in such databases. As the representation of 3D objects is no...
Marco Reisert, Hans Burkhardt
ESANN
2007
13 years 9 months ago
Classifying n-back EEG data using entropy and mutual information features
In this work we show that entropy (H) and mutual information (MI) can be used as methods for extracting spatially localized features for classification purposes. In order to incre...
Liang Wu, Predrag Neskovic, Etienne Reyes, Elena F...
ICCV
2009
IEEE
15 years 18 days ago
Wide-Baseline Image Matching Using Line Signatures
We present a wide-baseline image matching approach based on line segments. Line segments are clustered into local groups according to spatial proximity. Each group is treated as...
Lu Wang, Ulrich Neumann and Suya You
AFPAC
2000
Springer
341views Mathematics» more  AFPAC 2000»
13 years 12 months ago
An Associative Perception-Action Structure Using a Localized Space Variant Information Representation
Abstract. Most of the processing in vision today uses spatially invariant operations. This gives efficient and compact computing structures, with the conventional convenient separa...
Gösta H. Granlund
INFFUS
2008
97views more  INFFUS 2008»
13 years 7 months ago
Using classifier ensembles to label spatially disjoint data
act 11 We describe an ensemble approach to learning from arbitrarily partitioned data. The partitioning comes from the distributed process12 ing requirements of a large scale simul...
Larry Shoemaker, Robert E. Banfield, Lawrence O. H...