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ICCV
2003
IEEE
14 years 9 months ago
Feature Selection for Unsupervised and Supervised Inference: the Emergence of Sparsity in a Weighted-based Approach
The problem of selecting a subset of relevant features in a potentially overwhelming quantity of data is classic and found in many branches of science. Examples in computer vision...
Lior Wolf, Amnon Shashua
BMCBI
2008
160views more  BMCBI 2008»
13 years 7 months ago
Feature selection environment for genomic applications
Background: Feature selection is a pattern recognition approach to choose important variables according to some criteria in order to distinguish or explain certain phenomena (i.e....
Fabrício Martins Lopes, David Correa Martin...
ARTMED
2007
347views more  ARTMED 2007»
13 years 7 months ago
A combined MRI and MRSI based multiclass system for brain tumour recognition using LS-SVMs with class probabilities and feature
Objective: This study investigates the use of automated pattern recognition methods on magnetic resonance data with the ultimate goal to assist clinicians in the diagnosis of brai...
Jan Luts, Arend Heerschap, Johan A. K. Suykens, Sa...
IJCV
1998
238views more  IJCV 1998»
13 years 7 months ago
Feature Detection with Automatic Scale Selection
The fact that objects in the world appear in different ways depending on the scale of observation has important implications if one aims at describing them. It shows that the not...
Tony Lindeberg
CIARP
2009
Springer
14 years 2 months ago
Analysis of the GRNs Inference by Using Tsallis Entropy and a Feature Selection Approach
Abstract. An important problem in the bioinformatics field is to understand how genes are regulated and interact through gene networks. This knowledge can be helpful for many appl...
Fabrício Martins Lopes, Evaldo A. de Olivei...