Perspectives in machine learning for wildlife conservation

Perspectives in machine learning for wildlife conservation

Animal ecologists are increasingly limited by constraints in data processing. Here, Tuia and colleagues discuss how collaboration between ecologists and data scientists can harness machine learning to capitalize on the data generated from technological advances and lead to novel modeling approaches.

Bibliographic Details
Main Authors: Devis Tuia, Benjamin Kellenberger, Sara Beery, Blair R. Costelloe, Silvia Zuffi, Benjamin Risse, Alexander Mathis, Mackenzie W. Mathis, Frank van Langevelde, Tilo Burghardt, Roland Kays, Holger Klinck, Martin Wikelski, Iain D. Couzin, Grant van Horn, Margaret C. Crofoot, Charles V. Stewart, Tanya Berger-Wolf
Format: Article
Language:English
Published: Nature Portfolio 2022-02-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-022-27980-y

Internet

https://doi.org/10.1038/s41467-022-27980-y

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