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Artifact detection in SAR images with AI methods

Koslow, Wadim and Rack, Kathrin and Rüttgers, Alexander and Dell Amore, Luca and Rizzoli, Paola (2024) Artifact detection in SAR images with AI methods. In: Proceedings of the European Conference on Synthetic Aperture Radar, EUSAR, pp. 463-468. EUSAR 2024, 2024-04-23 - 2024-04-26, München, Deutschland. ISSN 2197-4403.

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Official URL: https://ieeexplore.ieee.org/abstract/document/10659585/metrics#metrics

Abstract

The increasing number of Earth observation data necessitates for advanced automated evaluation. Autoencoders (AE), which are deep neural networks, have been successfully applied to change detection on optical images. Here, we present an investigation of the applicability of three different convolutional AE methods for change detection on time series of SAR images. During the evaluation, the so-called joint AE approach is proved to be more precise and less sensitive to changes in brightness, thus designating less false positives. Moreover, the joint AE method indicates three noticeable and conspicuous regions.

Item URL in elib:https://elib.dlr.de/204392/
Document Type:Conference or Workshop Item (Speech, Poster, Other)
Title:Artifact detection in SAR images with AI methods
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Koslow, WadimUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Rack, KathrinUNSPECIFIEDhttps://orcid.org/0000-0002-5794-5705173106518
Rüttgers, AlexanderUNSPECIFIEDhttps://orcid.org/0000-0001-6347-9272UNSPECIFIED
Dell Amore, LucaUNSPECIFIEDhttps://orcid.org/0000-0002-6731-1300173106519
Rizzoli, PaolaUNSPECIFIEDhttps://orcid.org/0000-0001-9118-2732UNSPECIFIED
Date:2024
Journal or Publication Title:Proceedings of the European Conference on Synthetic Aperture Radar, EUSAR
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:No
Page Range:pp. 463-468
ISSN:2197-4403
Status:Published
Keywords:SAR, Machine Learning, Anomaly Detection, Change Detection
Event Title:EUSAR 2024
Event Location:München, Deutschland
Event Type:international Conference
Event Start Date:23 April 2024
Event End Date:26 April 2024
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 - Impulse project Resilient supply infrastructure and flows of goods in the context of extreme weather events near the coast
Location: Köln-Porz , Oberpfaffenhofen
Institutes and Institutions:Institute of Software Technology > High-Performance Computing
Institute of Software Technology
Microwaves and Radar Institute > Spaceborne SAR Systems
Deposited By: Koslow, Wadim
Deposited On:03 Jun 2024 14:08
Last Modified:20 Dec 2024 07:28

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