Deep learning and multi-station classification of volcano-seismic events of the Nevados del Chillán volcanic complex (Chile)
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-023-08994-z.pdf
Reference28 articles.
1. Curilem M, Canário JP, Franco L, Rios RA (2018) Using cnn to classify spectrograms of seismic events from llaima volcano (chile). In: 2018 International Joint Conference on Neural Networks (IJCNN), pp. 1–8. https://doi.org/10.1109/IJCNN.2018.8489285
2. Mou L, Jin Z (2018) Tree-based Convolutional Neural Networks: Principles and Applications. Springer, Singapore
3. Titos M, Bueno A, García L, Benítez MC, Ibañez J (2019) Detection and classification of continuous volcano-seismic signals with recurrent neural networks. IEEE Trans Geosci Remote Sens 57(4):1936–1948. https://doi.org/10.1109/TGRS.2018.2870202
4. Venegas P, Pèrez N, Benítez DS, Lara-Cueva R, Ruiz M (2019) Building machine learning models for long-period and volcano-tectonic event classification. In: 2019 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON), pp. 1–6. https://doi.org/10.1109/CHILECON47746.2019.8987505
5. Canário JP, Mello R, Curilem M, Huenupan F, Rios R (2020) In-depth comparison of deep artificial neural network architectures on seismic events classification. J Volcanol Geotherm Res 401:106881. https://doi.org/10.1016/j.jvolgeores.2020.106881
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