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Renaud, Claire (2022) Deep Learning for tracking Glacier Flows using TOPSAR data. Master's, ENSTA Bretagne.
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| Item URL in elib: | https://elib.dlr.de/188015/ | ||||||||
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| Document Type: | Thesis (Master's) | ||||||||
| Title: | Deep Learning for tracking Glacier Flows using TOPSAR data | ||||||||
| Authors: |
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| Date: | September 2022 | ||||||||
| Refereed publication: | Yes | ||||||||
| Open Access: | No | ||||||||
| Status: | Published | ||||||||
| Keywords: | InSAR, TOPS, interferometric phase, glacier flows | ||||||||
| Institution: | ENSTA Bretagne | ||||||||
| Department: | Observation Systems and Artificial Intelligence | ||||||||
| 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 - Aircraft SAR | ||||||||
| Location: | Oberpfaffenhofen | ||||||||
| Institutes and Institutions: | Microwaves and Radar Institute Microwaves and Radar Institute > SAR Technology | ||||||||
| Deposited By: | Pulella, M.Eng. Andrea | ||||||||
| Deposited On: | 06 Dec 2022 17:40 | ||||||||
| Last Modified: | 06 Dec 2022 17:40 |
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