A Transfer Learning Based Approach for Sunspot Detection
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-36258-3_37
Reference35 articles.
1. Mathieu, S., Lefèvre, L., von Sachs, R., Delouille, V., Ritter, C., Clette, F.: Nonparametric monitoring of sunspot number observations. J. Qual. Technol., 1–15 (2022). https://doi.org/10.1080/00224065.2022.2041376
2. Carvalho, S., Gomes, S., Barata, T., Lourenço, A., Peixinho, N.: Comparison of automatic methods to detect sunspots in the Coimbra observatory spectroheliograms. Astron. Comput. 32, 1–43 (2020). https://doi.org/10.1016/j.ascom.2020.100385
3. Yi, K., Moon, Y.-J., Lim, D., Park, E., Lee, H.: Visual explanation of a deep learning solar flare forecast model and its relationship to physical parameters. Astrophys. J. 910(1), 8 (2021). https://doi.org/10.3847/1538-4357/abdebe
4. Baek, J.-H., et al.: Solar event detection using deep-learning-based object detection methods. Sol. Phys. 296(11), 1–15 (2021). https://doi.org/10.1007/s11207-021-01902-5
5. Tan, M., Le, Q.V.: EfficientNet: rethinking model scaling for convolutional neural networks (2019)
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