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Deep Learning for Forest Canopy Height Estimation from SAR

Mahesh, Ragini Bal and Hänsch, Ronny (2023) Deep Learning for Forest Canopy Height Estimation from SAR. In: 2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2023-07-16 - 2023-07-21, Pasadena, USA.

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Item URL in elib:https://elib.dlr.de/195398/
Document Type:Conference or Workshop Item (Poster)
Title:Deep Learning for Forest Canopy Height Estimation from SAR
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Mahesh, Ragini BalUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Hänsch, RonnyUNSPECIFIEDhttps://orcid.org/0000-0002-2936-6765UNSPECIFIED
Date:31 May 2023
Journal or Publication Title:2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Accepted
Keywords:Deep Learning, Forest Height, InSAR
Event Title:IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
Event Location:Pasadena, USA
Event Type:international Conference
Event Dates:2023-07-16 - 2023-07-21
Organizer:IEEE GRSS
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 - Artificial Intelligence
Location: Oberpfaffenhofen
Institutes and Institutions:Microwaves and Radar Institute > SAR Technology
Deposited By: Hänsch, Ronny
Deposited On:03 Jul 2023 07:29
Last Modified:03 Jul 2023 07:29

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