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Neural-network pattern recognition experiments toward a full-automatic detection of anomalies in InSAR time-series of surface deformation

Milillo, Pietro and Sacco, Gianfranco and Di Martire, Diego and Hook, Hua (2021) Neural-network pattern recognition experiments toward a full-automatic detection of anomalies in InSAR time-series of surface deformation. Frontiers in Earth Science. Frontiers Media S.A.. doi: 10.3389/feart.2021.728643. ISSN 2296-6463.

Full text not available from this repository.

Official URL: https://www.frontiersin.org/articles/10.3389/feart.2021.728643/abstract


Item URL in elib:https://elib.dlr.de/146456/
Document Type:Article
Title:Neural-network pattern recognition experiments toward a full-automatic detection of anomalies in InSAR time-series of surface deformation
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Milillo, Pietropieto.milillo (at) dlr.deUNSPECIFIED
Sacco, GianfrancoGianfranco.Sacco (at) jpl.nasa.govUNSPECIFIED
Di Martire, Diegodiego.dimartire (at) unina.itUNSPECIFIED
Hook, Huahook.hua (at) jpl.nasa.govUNSPECIFIED
Date:November 2021
Journal or Publication Title:Frontiers in Earth Science
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In SCOPUS:Yes
In ISI Web of Science:Yes
DOI:10.3389/feart.2021.728643
Publisher:Frontiers Media S.A.
ISSN:2296-6463
Status:Published
Keywords:Deep Learning, InSAR, deformations
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 - Support TerraSAR-X/TanDEM-X operations
Location: Oberpfaffenhofen
Institutes and Institutions:Microwaves and Radar Institute
Microwaves and Radar Institute > Spaceborne SAR Systems
Deposited By: Rizzoli, Paola
Deposited On:30 Nov 2021 14:14
Last Modified:20 Dec 2021 18:32

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