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An Advanced Deep-Learning-Based Approach for Enhancing INSAR Parameters Estimation

Dell Amore, Luca and Costa, Giovanni and Carcereri, Daniel and Demir, Begüm and Rizzoli, Paola (2025) An Advanced Deep-Learning-Based Approach for Enhancing INSAR Parameters Estimation. In: International Geoscience and Remote Sensing Symposium (IGARSS). IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2025-08-03 - 2025-08-08, Brisbane, Australia.

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Item URL in elib:https://elib.dlr.de/215126/
Document Type:Conference or Workshop Item (Speech)
Title:An Advanced Deep-Learning-Based Approach for Enhancing INSAR Parameters Estimation
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Dell Amore, LucaUNSPECIFIEDhttps://orcid.org/0000-0002-6731-1300UNSPECIFIED
Costa, GiovanniUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Carcereri, DanielUNSPECIFIEDhttps://orcid.org/0000-0002-3956-1409UNSPECIFIED
Demir, BegümUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Rizzoli, PaolaUNSPECIFIEDhttps://orcid.org/0000-0001-9118-2732UNSPECIFIED
Date:2025
Journal or Publication Title:International Geoscience and Remote Sensing Symposium (IGARSS)
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:No
Status:Accepted
Keywords:InSAR phase, coherence, denoising, deep learning
Event Title:IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
Event Location:Brisbane, Australia
Event Type:international Conference
Event Start Date:3 August 2025
Event End Date:8 August 2025
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 - AI4SAR
Location: Oberpfaffenhofen
Institutes and Institutions:Microwaves and Radar Institute > Spaceborne SAR Systems
Deposited By: Dell Amore, Luca
Deposited On:14 Jul 2025 17:50
Last Modified:14 Jul 2025 17:50

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