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Perspectives on Individual Animal Identification from Biology and Computer Vision

Identifying individual animals is crucial for many biological investigations. In response to some of the limitations of current identification methods, new automated computer vision approaches have emerged with strong performance. Here, we review current advances of computer vision identification te...

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Detalles Bibliográficos
Autores principales: Vidal, Maxime, Wolf, Nathan, Rosenberg, Beth, Harris, Bradley P, Mathis, Alexander
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8490693/
https://www.ncbi.nlm.nih.gov/pubmed/34050741
http://dx.doi.org/10.1093/icb/icab107
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author Vidal, Maxime
Wolf, Nathan
Rosenberg, Beth
Harris, Bradley P
Mathis, Alexander
author_facet Vidal, Maxime
Wolf, Nathan
Rosenberg, Beth
Harris, Bradley P
Mathis, Alexander
author_sort Vidal, Maxime
collection PubMed
description Identifying individual animals is crucial for many biological investigations. In response to some of the limitations of current identification methods, new automated computer vision approaches have emerged with strong performance. Here, we review current advances of computer vision identification techniques to provide both computer scientists and biologists with an overview of the available tools and discuss their applications. We conclude by offering recommendations for starting an animal identification project, illustrate current limitations, and propose how they might be addressed in the future.
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spelling pubmed-84906932021-10-05 Perspectives on Individual Animal Identification from Biology and Computer Vision Vidal, Maxime Wolf, Nathan Rosenberg, Beth Harris, Bradley P Mathis, Alexander Integr Comp Biol Symposium Identifying individual animals is crucial for many biological investigations. In response to some of the limitations of current identification methods, new automated computer vision approaches have emerged with strong performance. Here, we review current advances of computer vision identification techniques to provide both computer scientists and biologists with an overview of the available tools and discuss their applications. We conclude by offering recommendations for starting an animal identification project, illustrate current limitations, and propose how they might be addressed in the future. Oxford University Press 2021-05-29 /pmc/articles/PMC8490693/ /pubmed/34050741 http://dx.doi.org/10.1093/icb/icab107 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Symposium
Vidal, Maxime
Wolf, Nathan
Rosenberg, Beth
Harris, Bradley P
Mathis, Alexander
Perspectives on Individual Animal Identification from Biology and Computer Vision
title Perspectives on Individual Animal Identification from Biology and Computer Vision
title_full Perspectives on Individual Animal Identification from Biology and Computer Vision
title_fullStr Perspectives on Individual Animal Identification from Biology and Computer Vision
title_full_unstemmed Perspectives on Individual Animal Identification from Biology and Computer Vision
title_short Perspectives on Individual Animal Identification from Biology and Computer Vision
title_sort perspectives on individual animal identification from biology and computer vision
topic Symposium
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8490693/
https://www.ncbi.nlm.nih.gov/pubmed/34050741
http://dx.doi.org/10.1093/icb/icab107
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