Windy events detection in big bioacoustics datasets using a pre-trained Convolutional Neural Network
Windy events detection in big bioacoustics datasets using a pre-trained Convolutional Neural Network
This repository includes the code and all relevant files used throughout our study. These encompass everything from the initial sheets of the whole acoustic dataset utilised for selecting the annotated dataset to the notebook (.ipynb) and the recordings employed in training the model. The .wav file are compressed in the file: wind-noise-detection-main.7z/data/208_file_recordings_paper_wind.tar
How to cite this work: Terranova, F., Betti, L., Ferrario, V., Friard, O., Ludynia, K., Petersen, G. S., Mathevon, N., Reby, D., & Favaro, L. (2024). Windy events detection in big bioacoustics datasets using a pre-trained Convolutional Neural Network. Science of The Total Environment, 949, 174868. https://doi.org/10.1016/j.scitotenv.2024.174868 (APA style)
- University of Turin Italy
- University of Cape Town South Africa
- Jean Monnet University France
- French National Centre for Scientific Research France
- Institut Universitaire de France France
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