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Simultaneous feature selection and Gaussian mixture model estimation for supervised classification problems

Kersten, Jens (2014) Simultaneous feature selection and Gaussian mixture model estimation for supervised classification problems. Pattern Recognition, 47 (8), pp. 2582-2595. Elsevier. DOI: http://dx.doi.org/10.1016/j.patcog.2014.02.015 ISSN 0031-3203

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Official URL: http://www.sciencedirect.com/science/article/pii/S0031320314000673


Item URL in elib:https://elib.dlr.de/88723/
Document Type:Article
Title:Simultaneous feature selection and Gaussian mixture model estimation for supervised classification problems
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Kersten, Jensjens.kersten (at) dlr.deUNSPECIFIED
Date:2014
Journal or Publication Title:Pattern Recognition
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:47
DOI :http://dx.doi.org/10.1016/j.patcog.2014.02.015
Page Range:pp. 2582-2595
Publisher:Elsevier
ISSN:0031-3203
Status:Published
Keywords:Gaussian mixture models; Clustering; Feature selection; Feature saliency; Expectation maximization; Supervised learning; Remote sensing
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Traffic Management (old)
DLR - Research area:Transport
DLR - Program:V VM - Verkehrsmanagement
DLR - Research theme (Project):V - Projekt VABENE (old)
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Geo Risks and Civil Security
Deposited By: Römer, Hannes
Deposited On:15 Apr 2014 13:45
Last Modified:08 Mar 2018 18:47

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