L*a*b*fruits : a rapid and robust outdoor fruit detection system combining bio-inspired features with one-stage deep learning networks

Kirk, R., Cielniak, G. and Mangan, M. orcid.org/0000-0002-0293-8874 (2020) L*a*b*fruits : a rapid and robust outdoor fruit detection system combining bio-inspired features with one-stage deep learning networks. Sensors, 20 (1). 275.

Abstract

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Authors/Creators:
Copyright, Publisher and Additional Information: © 2020 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 (http://creativecommons.org/licenses/by/4.0/).
Keywords: fruit detection; deep learning; computer vision; agricultural robotics; multi-modal; strawberry perception; fruit localisation; outdoor detection; bio-inspired; one-stage networks
Dates:
  • Accepted: 30 December 2019
  • Published (online): 3 January 2020
  • Published: 1 January 2020
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 11 Feb 2020 12:11
Last Modified: 11 Feb 2020 12:11
Status: Published
Publisher: MDPI
Refereed: Yes
Identification Number: https://doi.org/10.3390/s20010275

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