Augmenting biologging with supervised machine learning to study in situ behavior of the medusa Chrysaora fuscescens

Zooplankton play critical roles in marine ecosystems, yet their fine-scale behavior remains poorly understood because of the difficulty in studying individuals in situ. Here, we combine biologging with supervised machine learning (ML) to propose a pipeline for studying in situ behavior of larger zoo...

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Detalles Bibliográficos
Autores principales: Fannjiang, Clara, Mooney, T. Aran, Cones, Seth, Mann, David, Shorter, K. Alex, Katija, Kakani
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Company of Biologists Ltd 2019
Materias:
Methods & Techniques
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6739807/
https://www.ncbi.nlm.nih.gov/pubmed/31371399
http://dx.doi.org/10.1242/jeb.207654

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6739807/
https://www.ncbi.nlm.nih.gov/pubmed/31371399
http://dx.doi.org/10.1242/jeb.207654

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