Improving supernova detection by using YOLOv8 for astronomical image analysis
Author:
Funder
Türkiye Bilimsel ve Teknolojik Araştırma Kurumu
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11760-024-03438-0.pdf
Reference28 articles.
1. Adams, S.M., Kochanek, C.S., Gerke, J.R., Stanek, K.Z.: The search for failed supernovae with the large binocular telescope: constraints from 7 yr of data. Mon. Notices Royal Astronom. Soc. 469(2), 1445–1455 (2017). https://doi.org/10.1093/mnras/stx898
2. Wu, T.: A supernova detection implementation based on faster r-cnn, 390–393 (2020)
3. Yin, K., Jia, J., Gao, X., Sun, T., Zhou, Z.: Supernovae detection with fully convolutional one-stage framework. Sensors 21(5), 1926 (2021)
4. Yin, K., Jia, J., Li, F., Gao, X., Sun, T.: Harnessing edge-enhanced attention mechanisms for supernova detection in deep learning frameworks. Astron. Comput. 46, 100784 (2024). https://doi.org/10.1016/j.ascom.2023.100784
5. López, M., Di Palma, I., Drago, M., Cerdá-Durán, P., Ricci, F.: Deep learning for core-collapse supernova detection. Phys. Rev. D 103, 063011 (2021)
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