Behavioural inference from signal processing using animal-borne multi-sensor loggers: a novel solution to extend the knowledge of sea turtle ecology

Behavioural inference from signal processing using animal-borne multi-sensor loggers: a novel solution to extend the knowledge of sea turtle ecology

The identification of sea turtle behaviours is a prerequisite to predicting the activities and time-budget of these animals in their natural habitat over the long term. However, this is hampered by a lack of reliable methods that enable the detection and monitoring of certain key behaviours such as...

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Bibliographic Details
Main Authors: Lorène Jeantet, Víctor Planas-Bielsa, Simon Benhamou, Sebastien Geiger, Jordan Martin, Flora Siegwalt, Pierre Lelong, Julie Gresser, Denis Etienne, Gaëlle Hiélard, Alexandre Arque, Sidney Regis, Nicolas Lecerf, Cédric Frouin, Abdelwahab Benhalilou, Céline Murgale, Thomas Maillet, Lucas Andreani, Guilhem Campistron, Hélène Delvaux, Christelle Guyon, Sandrine Richard, Fabien Lefebvre, Nathalie Aubert, Caroline Habold, Yvon le Maho, Damien Chevallier
Format: Article
Language:English
Published: The Royal Society 2020-05-01
Series:Royal Society Open Science
Subjects:
supervised learning algorithms
accelerometer
sea turtle
animal-borne camera
behavioural classification
marine ecology
Online Access:https://royalsocietypublishing.org/doi/pdf/10.1098/rsos.200139

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https://royalsocietypublishing.org/doi/pdf/10.1098/rsos.200139

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