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HED-UNet: A multi-scale framework for simultaneous segmentation and edge detection

Heidler, Konrad and Mou, LiChao and Baumhoer, Celia and Dietz, Andreas and Zhu, Xiao Xiang (2021) HED-UNet: A multi-scale framework for simultaneous segmentation and edge detection. In: International Geoscience and Remote Sensing Symposium (IGARSS), pp. 1-4. IGARSS 2021, 12.-16. July 2021, Brussels, Belgium.

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Abstract

Segmentation models for remote sensing imagery are usually trained on the segmentation task alone. However, for many applications, the class boundaries carry semantic value. To account for this, we propose a new approach that unites both tasks within a single deep learning model. The proposed network architecture follows the successful encoder-decoder approach, and is improved by employing deep supervision at multiple resolution levels, as well as merging these resolution levels into a final prediction using a hierarchical attention mechanism. This framework is trained to detect the coastline in Sentinel-1 images of the Antarctic coastline. Its performance is then compared to conventional single-task approaches, and shown to outperform these methods. The code is available at https://github.com/khdlr/HED-UNet

Item URL in elib:https://elib.dlr.de/143088/
Document Type:Conference or Workshop Item (Speech)
Title:HED-UNet: A multi-scale framework for simultaneous segmentation and edge detection
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Heidler, KonradKonrad.Heidler (at) dlr.dehttps://orcid.org/0000-0001-8226-0727
Mou, LiChaoLiChao.Mou (at) dlr.dehttps://orcid.org/0000-0001-8407-6413
Baumhoer, CeliaCelia.Baumhoer (at) dlr.dehttps://orcid.org/0000-0003-1339-2288
Dietz, AndreasAndreas.Dietz (at) dlr.deUNSPECIFIED
Zhu, Xiao Xiangxiaoxiang.zhu (at) dlr.dehttps://orcid.org/0000-0001-5530-3613
Date:July 2021
Journal or Publication Title:International Geoscience and Remote Sensing Symposium (IGARSS)
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:No
Page Range:pp. 1-4
Status:Published
Keywords:Semantic segmentation, edge detection, Antarctica, glacier front
Event Title:IGARSS 2021
Event Location:Brussels, Belgium
Event Type:international Conference
Event Dates:12.-16. July 2021
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 - Artificial Intelligence
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > EO Data Science
German Remote Sensing Data Center > Land Surface Dynamics
Deposited By: Heidler, Konrad
Deposited On:19 Jul 2021 10:31
Last Modified:20 Jul 2021 10:56

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