Tell a friend
Print
Moliterni, Vito (2025) Deep learning-based estimation of bio-physical parameters from multifrequency airborne InSAR data. Master's, Politecnico di Milano.
Full text not available from this repository.
| Item URL in elib: | https://elib.dlr.de/203734/ | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Document Type: | Thesis (Master's) | ||||||||
| Title: | Deep learning-based estimation of bio-physical parameters from multifrequency airborne InSAR data | ||||||||
| Authors: |
| ||||||||
| Date: | March 2025 | ||||||||
| Open Access: | No | ||||||||
| Status: | Published | ||||||||
| Keywords: | sar, airborne, interferometry, deep learning, forestry, tropics | ||||||||
| Institution: | Politecnico di Milano | ||||||||
| Department: | Space Engineering | ||||||||
| 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 Microwaves and Radar Institute > Spaceborne SAR Systems | ||||||||
| Deposited By: | Carcereri, Daniel | ||||||||
| Deposited On: | 08 May 2024 18:22 | ||||||||
| Last Modified: | 01 Dec 2025 16:29 |
Repository Staff Only: item control page
