Deep neural networks for creating reliable PmP database with a case study in Southern California

Recent progresses in artificial intelligence and machine learning make it possible to automatically identify seismic phases from exponentially growing seismic data. Despite some exciting successes in automatic picking of the first P- and S-wave arrivals, auto-identification of later seismic phase...

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Bibliographic Details
Main Authors: Ding, Wen, Li, Tianjue, Yang, Xu, Ren, Kui, Tong, Ping
Other Authors: School of Physical and Mathematical Sciences
Format: Article
Language:English
Published: 2023
Subjects:
Online Access:https://hdl.handle.net/10356/170958
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Institution: Nanyang Technological University
Language: English
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