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Self-Supervised Convolutional Neural Networks for Plant Reconstruction Using Stereo Imagery

Xia, Yuanxin and Angelo, Pablo and Tian, Jiaojiao and Fraundorfer, Friedrich and Reinartz, Peter (2019) Self-Supervised Convolutional Neural Networks for Plant Reconstruction Using Stereo Imagery. Photogrammetric Engineering and Remote Sensing, 85 (5), pp. 389-399. American Society for Photogrammetry and Remote Sensing. doi: 10.14358/PERS.85.5.389. ISSN 0099-1112.

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Official URL: https://www.ingentaconnect.com/content/asprs/pers/2019/00000085/00000005/art00016


Item URL in elib:https://elib.dlr.de/126686/
Document Type:Article
Title:Self-Supervised Convolutional Neural Networks for Plant Reconstruction Using Stereo Imagery
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Xia, YuanxinYuanxin.Xia (at) dlr.deUNSPECIFIEDUNSPECIFIED
Angelo, PabloPablo.Angelo (at) dlr.dehttps://orcid.org/0000-0001-8541-3856UNSPECIFIED
Tian, JiaojiaoJiaojiao.Tian (at) dlr.dehttps://orcid.org/0000-0002-8407-5098UNSPECIFIED
Fraundorfer, Friedrichfraundorfer (at) icg.tugraz.atUNSPECIFIEDUNSPECIFIED
Reinartz, PeterPeter.Reinartz (at) dlr.dehttps://orcid.org/0000-0002-8122-1475UNSPECIFIED
Date:2019
Journal or Publication Title:Photogrammetric Engineering and Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:85
DOI:10.14358/PERS.85.5.389
Page Range:pp. 389-399
Publisher:American Society for Photogrammetry and Remote Sensing
ISSN:0099-1112
Status:Published
Keywords:Self-Supervised; Convolutional Neural Networks; Dense Matching; Plant Reconstruction; Semi-Global Matching
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Vorhaben hochauflösende Fernerkundungsverfahren (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Photogrammetry and Image Analysis
Deposited By: Xia, Yuanxin
Deposited On:05 Mar 2019 10:48
Last Modified:22 Nov 2023 06:54

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