Learning Occluded Branch Depth Maps in Forest Environments Using RGB-D Images
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| Titel: | Learning Occluded Branch Depth Maps in Forest Environments Using RGB-D Images |
|---|---|
| Autoren: | Geckeler, Christian, Aucone, Emanuele, Schnider, Yannick, Simeon, Andri, von Bassewitz, Jan-Philipp, Zhu, Yunying, Mintchev, Stefano, id_orcid:0 000-0001-6272-0212 |
| Quelle: | IEEE Robotics and Automation Letters, 9 (3) |
| Verlagsinformationen: | IEEE |
| Publikationsjahr: | 2024 |
| Bestand: | ETH Zürich Research Collection |
| Schlagwörter: | Deep learning for visual perception, Robotics and automation in agriculture and forestry, RGB-D perception |
| Beschreibung: | ISSN:2377-3766 |
| Publikationsart: | article in journal/newspaper |
| Dateibeschreibung: | application/application/pdf |
| Sprache: | English |
| Relation: | info:eu-repo/semantics/altIdentifier/wos/001167554600002; info:eu-repo/grantAgreement/SNF/Eccellenza/186865; http://hdl.handle.net/20.500.11850/659145 |
| DOI: | 10.3929/ethz-b-000659145 |
| Verfügbarkeit: | https://hdl.handle.net/20.500.11850/659145 https://doi.org/10.3929/ethz-b-000659145 |
| Rights: | info:eu-repo/semantics/openAccess ; http://rightsstatements.org/page/InC-NC/1.0/ ; In Copyright - Non-Commercial Use Permitted |
| Dokumentencode: | edsbas.ED5EAF2B |
| Datenbank: | BASE |
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