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

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

Abstract 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 iden...

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Bibliographic Details
Main Authors: Arnaud Cannet, Camille Simon-Chane, Mohammad Akhoundi, Aymeric Histace, Olivier Romain, Marc Souchaud, Pierre Jacob, Darian Sereno, Karine Mouline, Christian Barnabe, Frédéric Lardeux, Philippe Boussès, Denis Sereno
Format: Article
Language:English
Published: Nature Portfolio 2023-08-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-023-41114-4

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https://doi.org/10.1038/s41598-023-41114-4

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