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...

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Bibliografische Detailangaben

Hauptverfasser:	Shinya Katoh, Yoshihisa Iio, Hiromichi Nagao, Hiroshi Katao, Masayo Sawada, Kazuhide Tomisaka
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	SpringerOpen 2025-07-01
Schriftenreihe:	Earth, Planets and Space
Schlagworte:	Deep learning Phase picking Earthquake detection Manten network
Online-Zugang:	https://doi.org/10.1186/s40623-025-02249-y
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