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

The continuously growing amount of seismic data collected worldwide is outpacing our abilities for analysis, since to date, such datasets have been analyzed in a human-expert-intensive, supervised fashion. Moreover, analyses that are conducted can be strongly biased by the standard models employed b...

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Detalles Bibliográficos
Autores principales: Seydoux, Léonard, Balestriero, Randall, Poli, Piero, Hoop, Maarten de, Campillo, Michel, Baraniuk, Richard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7414231/
https://www.ncbi.nlm.nih.gov/pubmed/32769972
http://dx.doi.org/10.1038/s41467-020-17841-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7414231/
https://www.ncbi.nlm.nih.gov/pubmed/32769972
http://dx.doi.org/10.1038/s41467-020-17841-x

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