Deep learning and wing interferential patterns identify Anopheles species and discriminate amongst Gambiae complex species

We present a new and innovative identification method based on deep learning of the wing interferential patterns carried by mosquitoes of the Anopheles genus to classify and assign 20 Anopheles species, including 13 malaria vectors. We provide additional evidence that this approach can identify Anop...

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Detalles Bibliográficos
Autores principales: Cannet, Arnaud, Simon-Chane, Camille, Akhoundi, Mohammad, Histace, Aymeric, Romain, Olivier, Souchaud, Marc, Jacob, Pierre, Sereno, Darian, Mouline, Karine, Barnabe, Christian, Lardeux, Frédéric, Boussès, Philippe, Sereno, Denis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10457333/
https://www.ncbi.nlm.nih.gov/pubmed/37626130
http://dx.doi.org/10.1038/s41598-023-41114-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10457333/
https://www.ncbi.nlm.nih.gov/pubmed/37626130
http://dx.doi.org/10.1038/s41598-023-41114-4

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