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Seeing It All: Evaluating Supervised Machine Learning Methods for the Classification of Diverse Otariid Behaviours
Constructing activity budgets for marine animals when they are at sea and cannot be directly observed is challenging, but recent advances in bio-logging technology offer solutions to this problem. Accelerometers can potentially identify a wide range of behaviours for animals based on unique patterns...
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| Publicado no: | PLoS One |
|---|---|
| Main Authors: | , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Public Library of Science
2016
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5176164/ https://ncbi.nlm.nih.gov/pubmed/28002450 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0166898 |
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