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99
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ICASSP
2011
IEEE
14 years 4 months 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
97
Voted
BMCBI
2008
106views more  BMCBI 2008»
15 years 27 days 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...
86
Voted
ICDM
2008
IEEE
160views Data Mining» more  ICDM 2008»
15 years 7 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
81
Voted
WEBI
2009
Springer
15 years 7 months ago
Specialized Review Selection for Feature Rating Estimation
—On participatory Websites, users provide opinions about products, with both overall ratings and textual reviews. In this paper, we propose an approach to accurately estimate fea...
Chong Long, Jie Zhang, Minlie Huang, Xiaoyan Zhu, ...
93
Voted
VMV
2001
119views Visualization» more  VMV 2001»
15 years 2 months ago
Improving Feature Tracking by Robust Points of interest Selection
This paper deals with robust point features selection for tracking. The aim is to identify unreliable features since the first frame so to track them in all the sequence. We exten...
Chafik Kermad, Christophe Collewet