Active Learning in Multi-label Classification of Bioacoustic Data
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-70893-0_9
Reference26 articles.
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2. Boney, R., Ilin, A.: Semi-supervised and active few-shot learning with prototypical networks. arXiv preprint arXiv:1711.10856 (2017)
3. Cañas, J., Toro-Gómez, M., Sugai, L., et al.: A dataset for benchmarking neotropical anuran calls identification in passive acoustic monitoring. Sci. Data 10(1), 771 (2023). https://doi.org/10.1038/s41597-023-02666-2
4. Ghani, B., Denton, T., Kahl, S., Klinck, H.: Global birdsong embeddings enable superior transfer learning for bioacoustic classification. Sci. Rep. 13(1), 22876 (2023)
5. Hand, D.J., Till, R.J.: A simple generalisation of the area under the roc curve for multiple class classification problems. Mach. Learn. 45, 171–186 (2001)
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