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» Parallelizing Feature Selection
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MVA
2008
140views Computer Vision» more  MVA 2008»
15 years 3 months ago
An occlusion metric for selecting robust camera configurations
Vision based tracking systems for surveillance and motion capture rely on a set of cameras to sense the environment. The exact placement or configuration of these cameras can have...
Xing Chen, James Davis
113
Voted
GECCO
2009
Springer
148views Optimization» more  GECCO 2009»
15 years 10 months ago
An evolutionary approach to constructive induction for link discovery
This paper presents a genetic programming-based symbolic regression approach to the construction of relational features in link analysis applications. Specifically, we consider t...
Tim Weninger, William H. Hsu, Jing Xia, Waleed Alj...
148
Voted
IJDAR
2010
169views more  IJDAR 2010»
15 years 2 months ago
A Bayesian network for combining descriptors: application to symbol recognition
Inthispaper,weproposeadescriptorcombination method, which enables to improve significantly the recognition rate compared to the recognition rates obtained by each descriptor. This ...
Sabine Barrat, Salvatore Tabbone
168
Voted
CAIP
2001
Springer
293views Image Analysis» more  CAIP 2001»
15 years 8 months ago
A Markov Random Field Image Segmentation Model Using Combined Color and Texture Features
In this paper, we propose a Markov random field (MRF) image segmentation model which aims at combining color and texture features. The theoretical framework relies on Bayesian est...
Zoltan Kato, Ting-Chuen Pong
130
Voted
ICVS
2009
Springer
15 years 1 months ago
Boosting with a Joint Feature Pool from Different Sensors
This paper introduces a new way to apply boosting to a joint feature pool from different sensors, namely 3D range data and color vision. The combination of sensors strengthens the ...
Dominik Alexander Klein, Dirk Schulz, Simone Frint...