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A deep learning approach to InSAR phase estimation

Gobbi, Giorgia (2019) A deep learning approach to InSAR phase estimation. Master's, University of Trento.

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Item URL in elib:https://elib.dlr.de/126805/
Document Type:Thesis (Master's)
Title:A deep learning approach to InSAR phase estimation
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Gobbi, Giorgiagiorgia.gobbi (at) studenti.unitn.itUNSPECIFIED
Date:October 2019
Refereed publication:Yes
Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:InSAR Phase estimation, Deep Learning, Convolutional Neural Network, Synthetic Aperture Radar
Institution:University of Trento
Department:Department of Information Engineering and Computer Science
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 - SAR-Methodology
Location: Oberpfaffenhofen
Institutes and Institutions:Microwaves and Radar Institute > Spaceborne SAR Systems
Deposited By: Sica, Dr. Francescopaolo
Deposited On:12 Mar 2019 17:06
Last Modified:12 Nov 2019 15:50

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