Learning Occluded Branch Depth Maps in Forest Environments Using RGB-D Images

Covering over a third of all terrestrial land area, forests are crucial environments; as ecosystems, for farming, and for human leisure. However, they are challenging to access for environmental monitoring, for agricultural uses, and for search and rescue applications. To enter, aerial robots need t...

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Veröffentlicht in:	IEEE robotics and automation letters Jg. 9; H. 3; S. 2439 - 2446
Hauptverfasser:	Geckeler, Christian, Aucone, Emanuele, Schnider, Yannick, Simeon, Andri, von Bassewitz, Jan-Philipp, Zhu, Yunying, Mintchev, Stefano
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 01.03.2024
Schlagworte:	Data augmentation Datasets Environmental monitoring Foliage Forests Image reconstruction Pixels Rainforests Robots Trees
ISSN:	2377-3766, 2377-3766
Online-Zugang:	Volltext
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