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:

Authors	Institution or Email of Authors	Author's ORCID iD	ORCID Put Code
Mou, Lichao	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED
Zhu, Xiao Xiang	DLR-IMF/TUM-LMF	UNSPECIFIED	UNSPECIFIED

Date:

November 2018

Journal or Publication Title:

IEEE Transactions on Geoscience and Remote Sensing

Refereed publication:

Yes

Open Access:

Gold Open Access:

In SCOPUS:

Yes

In ISI Web of Science:

Yes

Volume:

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 - Earth Observation

DLR - Research theme (Project):

R - Vorhaben hochauflösende Fernerkundungsverfahren (old)

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:

08 Nov 2023 10:39

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