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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Vydané v:	IEEE robotics and automation letters Ročník 9; číslo 3; s. 2439 - 2446
Hlavní autori:	Geckeler, Christian, Aucone, Emanuele, Schnider, Yannick, Simeon, Andri, von Bassewitz, Jan-Philipp, Zhu, Yunying, Mintchev, Stefano
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 01.03.2024
Predmet:	Data augmentation Datasets Environmental monitoring Foliage Forests Image reconstruction Pixels Rainforests Robots Trees
ISSN:	2377-3766, 2377-3766
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