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Vehicle Instance Segmentation from Aerial Image and Video Using a Multi-Task Learning Residual Fully Convolutional Network

Mou, Lichao and Zhu, Xiao Xiang (2018) Vehicle Instance Segmentation from Aerial Image and Video Using a Multi-Task Learning Residual Fully Convolutional Network. IEEE Transactions on Geoscience and Remote Sensing, 56 (11), pp. 6699-6711. IEEE - Institute of Electrical and Electronics Engineers. DOI: 10.1109/TGRS.2018.2841808 ISSN 0196-2892

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Official URL: https://ieeexplore.ieee.org/document/8408520


Item URL in elib:https://elib.dlr.de/120130/
Document Type:Article
Title:Vehicle Instance Segmentation from Aerial Image and Video Using a Multi-Task Learning Residual Fully Convolutional Network
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Mou, Lichaolichao.mou (at) dlr.deUNSPECIFIED
Zhu, Xiao XiangDLR-IMF/TUM-LMFUNSPECIFIED
Date:November 2018
Journal or Publication Title:IEEE Transactions on Geoscience and Remote Sensing
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:56
DOI :10.1109/TGRS.2018.2841808
Page Range:pp. 6699-6711
Publisher:IEEE - Institute of Electrical and Electronics Engineers
ISSN:0196-2892
Status:Published
Keywords:Boundary-aware multi-task learning network, fully convolutional network (FCN), high-resolution remote sensing image/video, instance semantic segmentation, residual neural network (ResNet), vehicle detection.
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: Mou, LiChao
Deposited On:28 May 2018 14:11
Last Modified:10 Dec 2018 13:17

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