YOLO-behaviour: a simple, flexible framework to automatically quantify animal behaviours from videos

Chan, A.H.H. orcid.org/0000-0002-5405-7155, Putra, P. orcid.org/0000-0002-7632-375X, Schupp, H. orcid.org/0000-0002-1725-9129 et al. (11 more authors) (2025) YOLO-behaviour: a simple, flexible framework to automatically quantify animal behaviours from videos. Methods in Ecology and Evolution. ISSN 2041-210X

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Item Type: Article
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© 2025 The Author(s). This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. http://creativecommons.org/licenses/by/4.0/

Keywords: animal behaviour; behavioural recognition; computer vision; machine learning
Dates:
  • Published: 12 February 2025
  • Published (online): 12 February 2025
  • Accepted: 10 January 2025
  • Submitted: 28 August 2024
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Science (Sheffield) > School of Biosciences (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 19 Feb 2025 16:58
Last Modified: 19 Feb 2025 16:58
Status: Published online
Publisher: Wiley
Refereed: Yes
Identification Number: 10.1111/2041-210x.14502
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