Dataset for "Benchmarking for the automated detection of southern yellow-cheeked crested gibbon calls from passive acoustic monitoring data"
收藏NIAID Data Ecosystem2026-05-02 收录
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https://zenodo.org/record/12706802
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Abstract from paper in prep...
"Benchmarking for the automated detection of southern yellow-cheeked crested gibbon calls from passive acoustic monitoring data"
Recent advances in deep learning and transfer learning have revolutionized our ability for the automated detection of acoustic signals from long-term recordings. Here, we provide a benchmark for the automated detection of southern yellow-cheeked crested gibbon calls recorded using passive acoustic monitoring in Jahoo, Cambodia. We compared the performance of support vector machines, a quasi-DenseNet architecture (Koogu), transfer learning with ResNet50 models trained on the ‘ImageNet’ dataset, and transfer learning with embeddings from a global birdsong model (BirdNET). We also investigated the impact of varying the number of training samples on the performance of these models. We found that BirdNET had superior performance with a smaller number of training samples, whereas Koogu and ResNet50 models only had acceptable performance with a larger number of training samples ( > 200). Effective automated detection approaches are critical for monitoring endangered species, like gibbons. Future work on other gibbon species will be informative. Code and data are publicly available for future benchmarking.
Link to GitHub: https://github.com/DenaJGibbon/BirdNET-Performance-Comparison.
Please cite both if you use these data:
Clink, D., Cross-Jaya, H., Kim, J., Ahmad, A. H., Hong, M., Sala, R., Birot, H., Agger, C., Vu, T. T., Thi, H. N., Chi, T. N., & Klinck, H. (2024). Dataset for "Benchmarking for the automated detection of southern yellow-cheeked crested gibbon calls from passive acoustic monitoring data" [Data set]. Zenodo. https://doi.org/10.5281/zenodo.12706803
Clink DJ, Cross-Jaya H, Kim J, Ahmad AH, Hong M, Sala R, Birot H, Agger C, Vu TT, Thi HN, Chi TN. Benchmarking for the automated detection and classification of southern yellow-cheeked crested gibbon calls from passive acoustic monitoring data. bioRxiv. 2024:2024-08.
创建时间:
2024-08-22



