A deep learning application to map weed spatial extent from unmanned aerial vehicles imagery

Fraccaro, P., Butt, J., Edwards, B. et al. (4 more authors) (2022) A deep learning application to map weed spatial extent from unmanned aerial vehicles imagery. Remote Sensing, 14 (17). 4197. ISSN 2072-4292

Abstract

Metadata

Authors/Creators:
Copyright, Publisher and Additional Information: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Keywords: deep learning; image segmentation; unmanned aerial vehicle; weed detection; black-grass
Dates:
  • Accepted: 17 August 2022
  • Published (online): 26 August 2022
  • Published: 1 September 2022
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Science (Sheffield) > School of Biological Sciences (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 02 Sep 2022 19:44
Last Modified: 03 Sep 2022 20:25
Status: Published
Publisher: MDPI AG
Refereed: Yes
Identification Number: https://doi.org/10.3390/rs14174197

Share / Export

Statistics