Clustering earthquake signals and background noises in continuous seismic data with unsupervised deep learning

The authors here tackle the problem that too much seismic data is acquired worldwide to be evaluated in a timely fashion. Seydoux and colleagues develop a machine learning framework that can detect and cluster seismic signals in continuous seismic records.

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Detalles Bibliográficos
Autores principales: Léonard Seydoux, Randall Balestriero, Piero Poli, Maarten de Hoop, Michel Campillo, Richard Baraniuk
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2020
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Acceso en línea:https://doaj.org/article/a51cdd1b270c4f8196f7d797e88c4698
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