Deep learning models to identify penguins' prey capture rates

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.