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Virtual support vector machines with self-learning strategy for classification of multispectral remote sensing imagery

Geiß, Christian and Aravena Pelizari, Patrick and Blickensdörfer, Lukas and Taubenböck, Hannes (2019) Virtual support vector machines with self-learning strategy for classification of multispectral remote sensing imagery. ISPRS Journal of Photogrammetry and Remote Sensing, 151, pp. 42-58. Elsevier. ISSN 0924-2716

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Official URL: https://www.sciencedirect.com/science/article/abs/pii/S0924271619300620


Item URL in elib:https://elib.dlr.de/128299/
Document Type:Article
Title:Virtual support vector machines with self-learning strategy for classification of multispectral remote sensing imagery
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Geiß, ChristianChristian.Geiss (at) dlr.deUNSPECIFIED
Aravena Pelizari, PatrickPatrick.AravenaPelizari (at) dlr.deUNSPECIFIED
Blickensdörfer, LukasBlickensdoerfer.lukas (at) gmail.comUNSPECIFIED
Taubenböck, HannesHannes.Taubenboeck (at) dlr.deUNSPECIFIED
Date:2019
Journal or Publication Title:ISPRS Journal of Photogrammetry and Remote Sensing
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:151
Page Range:pp. 42-58
Publisher:Elsevier
ISSN:0924-2716
Status:Published
Keywords:ClassificationSupport Vector MachinesSelf-learningActive learning heuristicsVery high spatial resolution imagery
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Remote sensing and geoscience
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Geo Risks and Civil Security
Deposited By: Geiß, Christian
Deposited On:05 Aug 2019 10:19
Last Modified:06 Sep 2019 15:28

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