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

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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Bibliographic Details
Main Authors: Shinya Katoh, Yoshihisa Iio, Hiromichi Nagao, Hiroshi Katao, Masayo Sawada, Kazuhide Tomisaka
Format: Article
Language:English
Published: SpringerOpen 2025-07-01
Series:Earth, Planets and Space
Subjects:
Deep learning
Phase picking
Earthquake detection
Manten network
Online Access:https://doi.org/10.1186/s40623-025-02249-y
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https://doi.org/10.1186/s40623-025-02249-y

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