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ICPR
2006
IEEE
14 years 10 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...
ICASSP
2011
IEEE
13 years 24 days ago
SVM feature selection for multidimensional EEG data
In many machine learning applications, like Brain - Computer Interfaces (BCI), only high-dimensional noisy data are available rendering the discrimination task non-trivial. In thi...
Nisrine Jrad, Ronald Phlypo, Marco Congedo
BMCBI
2008
106views more  BMCBI 2008»
13 years 9 months ago
A machine vision system for automated non-invasive assessment of cell viability via dark field microscopy, wavelet feature selec
Background: Cell viability is one of the basic properties indicating the physiological state of the cell, thus, it has long been one of the major considerations in biotechnologica...
Ning Wei, Erwin Flaschel, Karl Friehs, Tim W. Natt...
ICDM
2008
IEEE
160views Data Mining» more  ICDM 2008»
14 years 3 months ago
Direct Zero-Norm Optimization for Feature Selection
Zero-norm, defined as the number of non-zero elements in a vector, is an ideal quantity for feature selection. However, minimization of zero-norm is generally regarded as a combi...
Kaizhu Huang, Irwin King, Michael R. Lyu
INCDM
2010
Springer
166views Data Mining» more  INCDM 2010»
13 years 7 months ago
Comparison of Redundancy and Relevance Measures for Feature Selection in Tissue Classification of CT Images
In this paper we report on a study on feature selection within the minimum
Benjamin Auffarth, Maite López, Jesú...