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Mazza, Antonio and Sica, Francescopaolo (2019) Deep Learning Solutions for TanDEM-X based forest classification. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2019-07-28 -2019-08-02, Yokohama, Japan.
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| Item URL in elib: | https://elib.dlr.de/127105/ | |||||||||
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| Document Type: | Conference or Workshop Item (Poster) | |||||||||
| Title: | Deep Learning Solutions for TanDEM-X based forest classification | |||||||||
| Authors: |
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| Date: | 2019 | |||||||||
| Refereed publication: | Yes | |||||||||
| Gold Open Access: | No | |||||||||
| In SCOPUS: | No | |||||||||
| In ISI Web of Science: | No | |||||||||
| Status: | Accepted | |||||||||
| Keywords: | Forest classification, InSAR, TanDEM-X, Deep Learning, Convolutional Neural Networks | |||||||||
| Event Title: | IEEE International Geoscience and Remote Sensing Symposium (IGARSS) | |||||||||
| Event Location: | Yokohama, Japan | |||||||||
| Event Type: | international Conference | |||||||||
| Event Dates: | 2019-07-28 -2019-08-02 | |||||||||
| HGF - Research field: | Aeronautics, Space and Transport | |||||||||
| HGF - Program: | Space | |||||||||
| HGF - Program Themes: | Earth Observation | |||||||||
| DLR - Research area: | Raumfahrt | |||||||||
| DLR - Program: | R EO - Erdbeobachtung | |||||||||
| DLR - Research theme (Project): | R - SAR-Methodology | |||||||||
| Location: | Oberpfaffenhofen | |||||||||
| Institutes and Institutions: | Microwaves and Radar Institute > Spaceborne SAR Systems | |||||||||
| Deposited By: | Sica, Dr. Francescopaolo | |||||||||
| Deposited On: | 09 Apr 2019 07:30 | |||||||||
| Last Modified: | 09 Apr 2019 07:30 |
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