Bio-logger Ethogram Benchmark: A benchmark for computational analysis of animal behavior, using animal-borne tags

This repository contains the datasets and experiment results presented in our arxiv paper:

B. Hoffman, M. Cusimano, V. Baglione, D. Canestrari, D. Chevallier, D. DeSantis, L. Jeantet, M. Ladds, T. Maekawa, V. Mata-Silva, V. Moreno-González, A. Pagano, E. Trapote, O. Vainio, A. Vehkaoja, K. Yoda, K. Zacarian, A. Friedlaender, “A benchmark for computational analysis of animal behavior, using animal-borne tags,” 2023.

Standardized code to implement, train, and evaluate models can be found at https://github.com/earthspecies/BEBE/. 

Please note the licenses in each dataset folder.

Zip folders beginning with “formatted”: These are the datasets we used to run the experiments reported in the benchmark paper. 

Zip folders beginning with “raw”: These are the unprocessed datasets used in BEBE. Code to process these raw datasets into the formatted ones used by BEBE can be found at https://github.com/earthspecies/BEBE-datasets/.

Zip folders beginning with “experiments”: Results of the cross-validation experiments reported in the paper, as well as hyperparameter optimization. Confusion matrices for all experiments can also be found here. Note that dt, rf, and svm refer to the feature set from Nathan et al., 2012.

Results used in Fig. 4 of arxiv paper (deep neural networks vs. classical models)
dataset_ harnet_nogyr
dataset_CRNN
dataset_CNN
dataset_dt
dataset_rf
dataset_svm
dataset_wavelet_dt
dataset_wavelet_rf
dataset_wavelet_svm

Results used in Fig. 5D of arxiv paper (full data setting)
If dataset contains gyroscope (HAR, jeantet_turtles, vehkaoja_dogs):
dataset_harnet_nogyr
dataset_harnet_random_nogyr
dataset_harnet_unfrozen_nogyr
dataset_RNN_nogyr
dataset_CRNN_nogyr
dataset_rf_nogyr

Otherwise:
dataset_harnet_nogyr
dataset_harnet_unfrozen_nogyr
dataset_harnet_random_nogyr
dataset_RNN_nogyr
dataset_CRNN
dataset_rf

Results used in Fig. 5E of arxiv paper (reduced data setting)
If dataset contains gyroscope (HAR, jeantet_turtles, vehkaoja_dogs):
dataset_harnet_low_data_nogyr
dataset_harnet_random_low_data_nogyr
dataset_harnet_unfrozen_low_data_nogyr
dataset_RNN_low_data_nogyr
dataset_wavelet_RNN_low_data_nogyr
dataset_CRNN_low_data_nogyr
dataset_rf_low_data_nogyr

Otherwise:
dataset_harnet_low_data_nogyr
dataset_harnet_random_low_data_nogyr
dataset_harnet_unfrozen_low_data_nogyr
dataset_RNN_low_data_nogyr
dataset_wavelet_RNN_low_data_nogyr
dataset_CRNN_l