SegPhase: development of arrival time picking models for Japan’s seismic network using the hierarchical vision transformer

Abstract Seismic phase picking is a fundamental task in seismology that is crucial for event detection and earthquake cataloging; however, manual analysis is impractical given the scale of modern seismic networks. We present SegPhase, a novel seismic arrival time picking model designed to efficientl...

Täydet tiedot

Bibliografiset tiedot

Päätekijät:	Shinya Katoh, Yoshihisa Iio, Hiromichi Nagao, Hiroshi Katao, Masayo Sawada, Kazuhide Tomisaka
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	SpringerOpen 2025-07-01
Sarja:	Earth, Planets and Space
Aiheet:	Deep learning Phase picking Earthquake detection Manten network
Linkit:	https://doi.org/10.1186/s40623-025-02249-y
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