The use of unmanned aerial vehicles (UAVs) in precision agriculture is gaining more and more interest. In this paper, we present a deep learning based method for estimating the crop and weed distribution from images captured by a UAV. The proposed approach runs on an embedded board equipped with a GPU. Quantitative experimental results have been obtained using real images from two different public datasets. The results demonstrate the effectiveness of the proposed approach. © Springer Nature Switzerland AG 2019.
UAV image based crop and weed distribution estimation on embedded GPU boards
Pretto A.;Nardi D.
2019
Abstract
The use of unmanned aerial vehicles (UAVs) in precision agriculture is gaining more and more interest. In this paper, we present a deep learning based method for estimating the crop and weed distribution from images captured by a UAV. The proposed approach runs on an embedded board equipped with a GPU. Quantitative experimental results have been obtained using real images from two different public datasets. The results demonstrate the effectiveness of the proposed approach. © Springer Nature Switzerland AG 2019.File in questo prodotto:
| File | Dimensione | Formato | |
|---|---|---|---|
|
Fawakherji_UAV_2019.pdf
non disponibili
Tipologia:
Published (publisher's version)
Licenza:
Accesso privato - non pubblico
Dimensione
1.7 MB
Formato
Adobe PDF
|
1.7 MB | Adobe PDF | Visualizza/Apri Richiedi una copia |
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
