Monocular Depth Estimation with Self-Supervised Learning for Vineyard Unmanned Agricultural Vehicle

To find an economical solution to infer the depth of the surrounding environment of unmanned agricultural vehicles (UAV), a lightweight depth estimation model called MonoDA based on a convolutional neural network is proposed. A series of sequential frames from monocular videos are used to train the...

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Detalles Bibliográficos
Autores principales: Cui, Xue-Zhi, Feng, Quan, Wang, Shu-Zhi, Zhang, Jian-Hua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8838921/
https://www.ncbi.nlm.nih.gov/pubmed/35161463
http://dx.doi.org/10.3390/s22030721

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8838921/
https://www.ncbi.nlm.nih.gov/pubmed/35161463
http://dx.doi.org/10.3390/s22030721

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