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Semantic Segmentation of Aerial Images with Explicit Class-Boundary Modeling

Marmanis, Dimitrios and Schindler, Konrad and Wegner, Jan Dirk and Datcu, Mihai and Stilla, Uwe (2017) Semantic Segmentation of Aerial Images with Explicit Class-Boundary Modeling. In: Proceedings of IGARSS 2017, pp. 5165-5168. IEEE Xplore. IGARSS 2017, 23.-28. Juli 2017, Fort Worth, TX, USA. DOI: 10.1109/IGARSS.2017.8128165 ISSN 2153-7003

Full text not available from this repository.

Official URL: http://ieeexplore.ieee.org/document/8128165/

Abstract

In this work we propose an end-to-end trainable supervised Deep Convolutional Neural Network (DCNN) targeting the task of semantic-segmentation with the addition of class-aware boundary detection. Through this explicit modeling of the class-boundaries, we enforce the network to extract coherent and complete objects, suppressing the uncertainty influencing these regions. Importantly, we show that class-boundary networks in conjunction with DCNN performs optimally, achieving over 90% overall accuracy (OA) on the challenging ISPRS Vaihingen Semantic Segmentation benchmark.

Item URL in elib:https://elib.dlr.de/118596/
Document Type:Conference or Workshop Item (Speech)
Title:Semantic Segmentation of Aerial Images with Explicit Class-Boundary Modeling
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Marmanis, DimitriosDimitrios.Marmanis (at) dlr.deUNSPECIFIED
Schindler, Konradkonrad.schindler (at) geod.baug.ethz.chUNSPECIFIED
Wegner, Jan DirkETH ZürichUNSPECIFIED
Datcu, Mihaimihai.datcu (at) dlr.deUNSPECIFIED
Stilla, Uwestilla (at) tum.deUNSPECIFIED
Date:July 2017
Journal or Publication Title:Proceedings of IGARSS 2017
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
DOI :10.1109/IGARSS.2017.8128165
Page Range:pp. 5165-5168
Publisher:IEEE Xplore
ISSN:2153-7003
Status:Published
Keywords:semantic-segmentation, CNN, FCN, VHSR, aerial imagery, Class-Boundary Modeling
Event Title:IGARSS 2017
Event Location:Fort Worth, TX, USA
Event Type:international Conference
Event Dates:23.-28. Juli 2017
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 > Photogrammetry and Image Analysis
Deposited By: Zielske, Mandy
Deposited On:01 Feb 2018 18:40
Last Modified:01 Feb 2018 18:40

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