Dataset for: Automated detection of gibbon calls from passive acoustic monitoring data using convolutional neural networks in the "torch for R" ecosystem.

This is the supporting data for: Clink, Dena J., et al. "Automated detection of gibbon calls from passive acoustic monitoring data using convolutional neural networks in the "torch for R" ecosystem." arXiv preprint arXiv:2407.09976 (2024). Link to GitHub Repository: https://github.com/DenaJGibbon/torch-for-R-gibbons Summary of data and scripts. To run the scripts download the data from Zenodo and add to your project directory. R Script Summary of Referenced Folders Top-Level Data or Results Folders Referenced Part 1a. Variability benchmarking results Training/test image folders (Danum, Jahoo, Combined); model run results for variability benchmarking. data/training_images_sorted/, results/part1/ Part 1b. Evaluate variability benchmarking results Evaluation output folders. results/part1/ Part 2a. Train CNNs over multiple epochs Training/test data for all sites; performance outputs for initial CNN evaluations (Cambodia, Malaysia). data/training_images_sorted/, results/part2/ Part 2b. Train CNNs (cont.) Model output folders (binary & multi-class); rerun AUC updates; model type labels. results/part2/ Part 3a. Data augmentation Augmented training images (Danum, Jahoo, Combined); test sets; model run outputs based on augmented data. data/DataAugmentation/, data/training_images_sorted/, results/part3/ Part 3b. Evaluation data augmentation Outputs from evaluating models trained on augmented data; model labels by type. results/part3/ Part 3c. Eval. augmentation on different test set Evaluation outputs for external test data (Maliau + Vietnam); multi-class model run outputs. TestData/, results/part3/ Part 4b. Comparison with BirdNET BirdNET outputs for Jahoo, Danum, and Combined data; test output from jittered data augmentation. results/part4/, results/part3/ Part 5. Final model performance Final evaluation images (per site); top-performing model folders; final performance CSVs. data/CombinedImagesWAEvaluation/, results/part5/ Part 6. Deploy Model over PAM data Longer sound files (Jahoo); final trained model checkpoint (.pt file) used for inference. data/WideArrayEvaluation/, results/part3/ Part 7. Call Density Plots Files for call density visualizations: GPS, selections, manually verified wavs or images (TP/FP). data/calldensityplots/