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Deep learning models to identify penguins' prey capture rates

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posted on 2024-03-15, 10:53 authored by Stefan SchoombieStefan Schoombie

We determined how well deep learning models would work to predict individual prey capture events from tri-axial accelerometer data collected from Chinstrap Penguins. This as done in the Python programming language.

Two models were trained (CNN and V-Net architectures) and predictions were made on individual birds that have not been exposed to the model training.

The resources include all the source code to produce the figures in the associated publication, as well as example data to run the scripts on.


Funding

Sustainable and predictable future for fisheries in Antarctica.Developing a scientifically based, data driven krill management system

The Research Council of Norway

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Antarctic Wildlife Research Fund (project no. 18/2021)

History

Department/Unit

Centre for Statistics in Ecology, Environment and Conservation (SEEC), Department of Statistical Sciences, University of Cape Town

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