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ZENODO
Dataset . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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Claim

Real-Time Earthquake Monitoring with Deep Learning: A Case Study of the 2025 M6.4 Dapu Earthquake in Southwestern Taiwan

Research datakeyboard_double_arrow_right Dataset 24 Feb 2025Publisher:Zenodo
Authors: Kuo-Chen, Hao; Sun, Wei-Fang; Kan, Li-Yu; Guan, Zhuo-Kang; Pan, Sheng-Yan; Liu, Yao-Hung;

doi: 10.5281/zenodo.14915424 , 10.5281/zenodo.14915423

Real-Time Earthquake Monitoring with Deep Learning: A Case Study of the 2025 M6.4 Dapu Earthquake in Southwestern Taiwan

Abstract

3D NonLinLoc earthquake catalog for the 2025 ML6.4 Dapu earthquake sequence from January 20 to February 3, 2025.

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    popularity
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    influence
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average