‘gibbonNetR’ contains functions for the automated detection and classification of acoustic signals. A brief summary of the functions is shown below.
| File Name | Description |
|---|---|
| deploy_CNN_binary.R | Deploys a trained binary CNN model over a directory of sound files |
| deploy_CNN_multi.R | Deploys a trained multi-class CNN model over a directory of sound files |
| evaluate_trainedmodel_performance_multi.R | Evaluates performance of a multi-class model on a test dataset |
| evaluate_trainedmodel_performance.R | Evaluates performance of a binary model on a test dataset |
| extract_embeddings.R | Extracts feature embeddings from trained models |
| get_best_performance.R | A function that benchmarks multiple trained models |
| spectrogram_images.R | Generates and processes spectrogram images |
| train_CNN_binary.R | Trains a binary classification CNN model |
| train_CNN_multi.R | Trains a multi-class classification CNN model |