This paper presents a fully automated procedure for the detection of trees affected by Xylella Fastidiosa using UAVs and convolutional neural networks. Drones are able to collect an adequate number of olive leaf images to detect the presence of disease symptoms. Several neural networks are trained to compare results and determine the best solution.

UAV Inspection of Olive Trees for the Detection of Xylella Fastidiosa Disease Using Neural Networks

Blanco I.;De Bellis L.;Luvisi A.
Ultimo
2021-01-01

Abstract

This paper presents a fully automated procedure for the detection of trees affected by Xylella Fastidiosa using UAVs and convolutional neural networks. Drones are able to collect an adequate number of olive leaf images to detect the presence of disease symptoms. Several neural networks are trained to compare results and determine the best solution.
2021
978-1-6654-3948-0
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11587/464968
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 3
  • ???jsp.display-item.citation.isi??? ND
social impact