Tell a friend
Print
Schlegel, Anastasia (2022) Interpretable Deep Learning in Remote Sensing: Case-Based Object Recognition in SAR and Optical Imagery. Master's, Technische Universität Berlin.
Full text not available from this repository.
| Item URL in elib: | https://elib.dlr.de/187823/ | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Document Type: | Thesis (Master's) | ||||||||
| Title: | Interpretable Deep Learning in Remote Sensing: Case-Based Object Recognition in SAR and Optical Imagery | ||||||||
| Authors: |
| ||||||||
| Date: | December 2022 | ||||||||
| Refereed publication: | Yes | ||||||||
| Open Access: | No | ||||||||
| Gold Open Access: | No | ||||||||
| In SCOPUS: | No | ||||||||
| In ISI Web of Science: | No | ||||||||
| Status: | Published | ||||||||
| Keywords: | Deep Learning, SAR | ||||||||
| Institution: | Technische Universität Berlin | ||||||||
| Department: | Computer Vision and Remote Sensing | ||||||||
| 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 > SAR Technology | ||||||||
| Deposited By: | Schlegel, Anastasia | ||||||||
| Deposited On: | 16 Aug 2022 07:14 | ||||||||
| Last Modified: | 06 Dec 2022 18:43 |
Repository Staff Only: item control page
