Carcereri, Daniel (2021) Deep learning-based multi-sensor fusion for forest height estimation. 10th Advanced Training Course on Land Remote Sensing, 2021-09-20 - 2021-09-24, Ljubljana, Slovenia.
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Item URL in elib: | https://elib.dlr.de/143547/ | ||||||
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Document Type: | Conference or Workshop Item (Poster) | ||||||
Title: | Deep learning-based multi-sensor fusion for forest height estimation | ||||||
Authors: |
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Date: | 24 September 2021 | ||||||
Refereed publication: | No | ||||||
Open Access: | No | ||||||
Gold Open Access: | No | ||||||
In SCOPUS: | No | ||||||
In ISI Web of Science: | No | ||||||
Status: | Published | ||||||
Keywords: | sar, forest height, deep learning | ||||||
Event Title: | 10th Advanced Training Course on Land Remote Sensing | ||||||
Event Location: | Ljubljana, Slovenia | ||||||
Event Type: | Workshop | ||||||
Event Dates: | 2021-09-20 - 2021-09-24 | ||||||
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 Microwaves and Radar Institute | ||||||
Deposited By: | Carcereri, Daniel | ||||||
Deposited On: | 20 Aug 2021 06:11 | ||||||
Last Modified: | 05 Dec 2022 15:09 |
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