Using Machine Learning for Remote Behaviour Classification—Verifying Acceleration Data to Infer Feeding Events in Free-Ranging Cheetahs

Behavioural studies of elusive wildlife species are challenging but important when they are threatened and involved in human-wildlife conflicts. Accelerometers (ACCs) and supervised machine learning algorithms (MLAs) are valuable tools to remotely determine behaviours. Here we used five captive chee...

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Detalles Bibliográficos
Autores principales: Giese, Lisa, Melzheimer, Jörg, Bockmühl, Dirk, Wasiolka, Bernd, Rast, Wanja, Berger, Anne, Wachter, Bettina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8398415/
https://www.ncbi.nlm.nih.gov/pubmed/34450868
http://dx.doi.org/10.3390/s21165426

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8398415/
https://www.ncbi.nlm.nih.gov/pubmed/34450868
http://dx.doi.org/10.3390/s21165426

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