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ICPR
2008
IEEE
14 years 5 months ago
A method of feature selection using contribution ratio based on boosting
AdaBoost and support vector machines (SVM) algorithms are commonly used in the field of object recognition. As classifiers, their classification performance is sensitive to affect...
Masamitsu Tsuchiya, Hironobu Fujiyoshi
ICPR
2006
IEEE
14 years 5 months ago
Boosted Band Ratio Feature Selection for Hyperspectral Image Classification
Band ratios have many useful applications in hyperspectral image analysis. While optimal ratios have been chosen empirically in previous research, we propose a principled algorith...
Antonio Robles-Kelly, Nianjun Liu, Terry Caelli, Z...
ICPR
2010
IEEE
13 years 7 months ago
Detecting Faint Compact Sources Using Local Features and a Boosting Approach
Several techniques have been proposed so far in order to perform faint compact source detection in wide field interferometric radio images. However, all these methods can easily mi...
Albert Torrent, Marta Peracaula, Xavier Llado, Jor...
ICASSP
2007
IEEE
13 years 11 months ago
Feature Selection Based on Fisher Ratio and Mutual Information Analyses for Robust Brain Computer Interface
This paper proposes a novel feature selection method based on twostage analysis of Fisher Ratio and Mutual Information for robust Brain Computer Interface. This method decomposes ...
Tran Huy Dat, Cuntai Guan
ISDA
2009
IEEE
13 years 11 months ago
Clustering-Based Feature Selection in Semi-supervised Problems
— In this contribution a feature selection method in semi-supervised problems is proposed. This method selects variables using a feature clustering strategy, using a combination ...
Ianisse Quinzán, José Manuel Sotoca,...