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Hyperspectral and LiDAR Fusion Using Deep Three-Stream Convolutional Neural Networks

Li, Hao and Ghamisi, Pedram and Soergel, Uwe and Zhu, Xiao Xiang (2018) Hyperspectral and LiDAR Fusion Using Deep Three-Stream Convolutional Neural Networks. Remote Sensing (10), pp. 1649-1668. Multidisciplinary Digital Publishing Institute (MDPI). DOI: 10.3390/rs10101649 ISSN 2072-4292

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Official URL: https://www.mdpi.com/2072-4292/10/10/1649


Item URL in elib:https://elib.dlr.de/122440/
Document Type:Article
Title:Hyperspectral and LiDAR Fusion Using Deep Three-Stream Convolutional Neural Networks
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Li, Haoleebobgiser316 (at) gmail.comUNSPECIFIED
Ghamisi, PedramDLR-IMF/TUM-LMFUNSPECIFIED
Soergel, Uwesoergel (at) ifp.uni-stuttgart.deUNSPECIFIED
Zhu, Xiao XiangDLR-IMF/TUM-LMFUNSPECIFIED
Date:2018
Journal or Publication Title:Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In SCOPUS:Yes
In ISI Web of Science:No
DOI :10.3390/rs10101649
Page Range:pp. 1649-1668
Publisher:Multidisciplinary Digital Publishing Institute (MDPI)
ISSN:2072-4292
Status:Published
Keywords:Feature Extraction, sentinel-1, local climate zones, lcz
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 - Vorhaben hochauflösende Fernerkundungsverfahren
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > EO Data Science
Deposited By: Häberle, Matthias
Deposited On:20 Nov 2018 10:43
Last Modified:21 Nov 2019 05:05

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