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CVPR
2003
IEEE
14 years 9 months ago
Kullback-Leibler Boosting
In this paper, we develop a general classification framework called Kullback-Leibler Boosting, or KLBoosting. KLBoosting has following properties. First, classification is based o...
Ce Liu, Heung-Yeung Shum
ICCV
2005
IEEE
14 years 9 months ago
Appearance Modeling Under Geometric Context
We propose a unified framework based on a general definition of geometric transform (GeT) for modeling appearance. GeT represents the appearance by applying designed functionals o...
Jian Li, Shaohua Kevin Zhou, Rama Chellappa
ICIP
2006
IEEE
14 years 1 months ago
Modelization of Limb Coordination for Human Action Analysis
This paper analyzes the movements of the human body limbs (hands, feet and head) and center of gravity in order to detect simple actions such as walking, jumping and displacing an...
Kosta Gaitanis, Pedro Correa, Benoit M. Macq
ESANN
2007
13 years 9 months ago
How to process uncertainty in machine learning?
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
Barbara Hammer, Thomas Villmann
VLSISP
2010
254views more  VLSISP 2010»
13 years 6 months ago
Manifold Based Local Classifiers: Linear and Nonlinear Approaches
Abstract In case of insufficient data samples in highdimensional classification problems, sparse scatters of samples tend to have many ‘holes’—regions that have few or no nea...
Hakan Cevikalp, Diane Larlus, Marian Neamtu, Bill ...