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Large-scale Building Height Estimation from Single VHR SAR image Using Fully Convolutional Network and GIS building footprints

Sun, Yao and Hua, Yuansheng and Mou, LiChao and Zhu, Xiaoxiang (2019) Large-scale Building Height Estimation from Single VHR SAR image Using Fully Convolutional Network and GIS building footprints. In: 2019 Joint Urban Remote Sensing Event (JURSE), pp. 1-4. JURSE 2019, 22. - 24. Mai 2019, Vannes, France. DOI: 10.1109/JURSE.2019.8809037

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Official URL: https://ieeexplore.ieee.org/document/8809037


Item URL in elib:https://elib.dlr.de/126331/
Document Type:Conference or Workshop Item (Speech)
Title:Large-scale Building Height Estimation from Single VHR SAR image Using Fully Convolutional Network and GIS building footprints
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Sun, Yaoyao.sun (at) dlr.deUNSPECIFIED
Hua, YuanshengYuansheng.Hua (at) dlr.deUNSPECIFIED
Mou, LiChaoLiChao.Mou (at) dlr.deUNSPECIFIED
Zhu, Xiaoxiangxiao.zhu (at) dlr.deUNSPECIFIED
Date:2019
Journal or Publication Title:2019 Joint Urban Remote Sensing Event (JURSE)
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
DOI :10.1109/JURSE.2019.8809037
Page Range:pp. 1-4
Status:Published
Keywords:building heights, large-scale, SAR, GIS, deep neural network
Event Title:JURSE 2019
Event Location:Vannes, France
Event Type:international Conference
Event Dates:22. - 24. Mai 2019
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: Sun, Yao
Deposited On:06 Dec 2019 13:28
Last Modified:06 Dec 2019 13:28

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