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Performance of Deep Learning Pickers in Routine Network Processing Applications

https://doi.org/10.1785/0220210323
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/wics.1460openalex-snapshot
The Akaike information criterion: Background, derivation, properties, application, interpretation, and refinements
inferredcites →https://doi.org/10.1007/s10950-006-2296-6openalex-snapshot
Automatic picking of P and S phases using a neural tree
inferredcites →https://doi.org/10.1016/j.pepi.2016.03.006openalex-snapshot
Improving the location of induced earthquakes associated with an underground gas storage in the Gulf of Valencia (Spain)
inferredcites →https://doi.org/10.1029/2012gl051846openalex-snapshot
Monitoring the volcanic unrest of El Hierro (Canary Islands) before the onset of the 2011–2012 submarine eruption
inferredcites →https://doi.org/10.1029/2017jb015251openalex-snapshot
P Wave Arrival Picking and First‐Motion Polarity Determination With Deep Learning
inferredcites →https://doi.org/10.1029/2019jb017536openalex-snapshot
Deep Learning for Picking Seismic Arrival Times
inferredcites →https://doi.org/10.1029/2020gl088651openalex-snapshot
Using a Deep Neural Network and Transfer Learning to Bridge Scales for Seismic Phase Picking
inferredcites →https://doi.org/10.1029/2021jb023499openalex-snapshot
Which Picker Fits My Data? A Quantitative Evaluation of Deep Learning Based Seismic Pickers
inferredcites →https://doi.org/10.1038/s41467-020-17591-wopenalex-snapshot
Earthquake transformer—an attentive deep-learning model for simultaneous earthquake detection and phase picking
inferredcites →https://doi.org/10.1093/gji/ggy423openalex-snapshot
PhaseNet: A Deep-Neural-Network-Based Seismic Arrival Time Picking Method
inferredcites →https://doi.org/10.1109/access.2019.2947848openalex-snapshot
STanford EArthquake Dataset (STEAD): A Global Data Set of Seismic Signals for AI
inferredcites →https://doi.org/10.1109/tgrs.2019.2911402openalex-snapshot
Seismic Phase Picking Using Convolutional Networks
inferredcites →https://doi.org/10.1111/1365-2478.12125openalex-snapshot
Novel hybrid artificial neural network based autopicking workflow for passive seismic data
inferredcites →https://doi.org/10.1190/geo2011-0301.1openalex-snapshot
Strategy for automated analysis of passive microseismic data based on S-transform, Otsu’s thresholding, and higher order statistics
inferredcites →https://doi.org/10.1190/geo2012-0050.1openalex-snapshot
A new automatic S-onset detection technique: Application in local earthquake data
inferredcites →https://doi.org/10.1785/0120120347openalex-snapshot
An Automatic Kurtosis-Based P- and S-Phase Picker Designed for Local Seismic Networks
inferredcites →https://doi.org/10.1785/0120180080openalex-snapshot
Generalized Seismic Phase Detection with Deep Learning
inferredcites →https://doi.org/10.1785/0220180308openalex-snapshot
Seismic Event and Phase Detection Using Time–Frequency Representation and Convolutional Neural Networks
inferredcites →https://doi.org/10.1785/0220180319openalex-snapshot
Hybrid Event Detection and Phase‐Picking Algorithm Using Convolutional and Recurrent Neural Networks
inferredcites →https://doi.org/10.1785/0220190052openalex-snapshot
Rapid Earthquake Association and Location
inferredcites →https://doi.org/10.1785/0220190313openalex-snapshot
Seismological Observatory Software: 30 Yr of SEISAN
inferredcites →https://doi.org/10.1785/0220200178openalex-snapshot
Leveraging Deep Learning in Global 24/7 Real-Time Earthquake Monitoring at the National Earthquake Information Center
inferredcites →https://doi.org/10.1785/bssa0680051521openalex-snapshot
Automatic earthquake recognition and timing from single traces
inferredcites →https://doi.org/10.20350/digitalcsic/14010openalex-snapshot
Analysis of the performance of Deep Learning automatic phase pickers for earthquake data [Dataset]
inferredcites →https://doi.org/10.29382/q20210038openalex-snapshot
Comparison of the earthquake detection effects of phaseNet and EQTransformer considering the Yangbi and Maduo Earthquakes
inferredcites →https://doi.org/10.3997/2214-4609.201800049openalex-snapshot
Integration Of Passive Seismic Methodologies And Its Application On The Maupasacq Dataset
inferredcites →https://doi.org/10.5194/se-11-63-2020openalex-snapshot
Fault reactivation by gas injection at an underground gas storage off the east coast of Spain

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Unveiling the pre-eruptive seismic series of the La Palma 2021 eruption: Insights through a fully automated analysis
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Crustal imaging and characterization of active faults with a large-N nodal deployment - Application to the Chaînons Béarnais region (western Pyrenees foothills, France)
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inferred← citeshttps://doi.org/10.1029/2022jb024918openalex-snapshot
Seismicity, Fault Architecture, and Slip Mode of the Westernmost Gofar Transform Fault
inferred← citeshttps://doi.org/10.1029/2023jb026793openalex-snapshot
New Insights Into the Active Tectonics of the Northern Canadian Cordillera From an Enhanced Earthquake Catalog
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inferred← citeshttps://doi.org/10.1029/2025jb031644openalex-snapshot
Seismicity From Modern Magmatic Activity Beneath Taupō Volcano, Aotearoa New Zealand
inferred← citeshttps://doi.org/10.1093/gji/ggae298openalex-snapshot
Deep learning models for regional phase detection on seismic stations in Northern Europe and the European Arctic
inferred← citeshttps://doi.org/10.1093/gji/ggaf136openalex-snapshot
KVP: a multiscale kurtosis approach for seismic phase picking
inferred← citeshttps://doi.org/10.1186/s40623-024-01982-0openalex-snapshot
Recent advances in earthquake seismology using machine learning
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Neural phase picker trained on the Japan meteorological agency unified earthquake catalog
inferred← citeshttps://doi.org/10.1186/s40623-025-02249-yopenalex-snapshot
SegPhase: development of arrival time picking models for Japan’s seismic network using the hierarchical vision transformer
inferred← citeshttps://doi.org/10.1785/0120220229openalex-snapshot
A Detailed View of the 2020–2023 Southwestern Puerto Rico Seismic Sequence with Deep Learning
inferred← citeshttps://doi.org/10.1785/0120230068openalex-snapshot
A Deep-Learning Phase Picker with Calibrated Bayesian-Derived Uncertainties for Earthquakes in the Yellowstone Volcanic Region
inferred← citeshttps://doi.org/10.1785/0120230128openalex-snapshot
Achieving a Comprehensive Microseismicity Catalog through a Deep-Learning-Based Workflow: Applications in the Central Ecuadorian Subduction Zone
inferred← citeshttps://doi.org/10.1785/0120230134openalex-snapshot
Deep Learning-Based Microseismic Detection and Location Reveal the Seismic Characteristics and Causes in the Xiluodu Reservoir, China
inferred← citeshttps://doi.org/10.1785/0220230161openalex-snapshot
An Efficient Transfer Learning-Based OBS Seismic Phase Picker (OBSPD) Trained on Cascadia Subduction Zone Earthquake Dataset
inferred← citeshttps://doi.org/10.1785/0220230182openalex-snapshot
A Practical Approach to Automatic Earthquake Catalog Compilation in Local OBS Networks Using Deep-Learning and Network-Based Algorithms
inferred← citeshttps://doi.org/10.1785/0220240186openalex-snapshot
surfQuake: A New Python Toolbox for the Workflow Process of Seismic Sources
inferred← citeshttps://doi.org/10.1785/0220250368openalex-snapshot
SCMLPick: A SeisComP Module Implementing Machine Learning Phase Picking for Real-Time Seismic Monitoring
inferred← citeshttps://doi.org/10.1785/0320230024openalex-snapshot
Parametric Testing of EQTransformer’s Performance against a High-Quality, Manually Picked Catalog for Reliable and Accurate Seismic Phase Picking
inferred← citeshttps://doi.org/10.21203/rs.3.rs-8174647/v1openalex-snapshot
PhaseNeXt: Neural phase picker trained on 20-year records to process the JMA-unified data set
inferred← citeshttps://doi.org/10.21203/rs.3.rs-8988784/v1openalex-snapshot
Application of automated seismic event detection in a low seismicity region of the Baltic States
inferred← citeshttps://doi.org/10.3389/feart.2023.1306488openalex-snapshot
Customization of a deep neural network using local data for seismic phase picking
inferred← citeshttps://doi.org/10.3390/app16168307openalex-snapshot
Seismic Event Detection in the Valencian Community Seismic Network Using the Wavelet Scattering Transform, PCA, and SVM: A Robust Lightweight Alternative to Deep Learning for Local Seismic Networks
inferred← citeshttps://doi.org/10.3390/geosciences15110436openalex-snapshot
The SISMIKO Monitoring Network and Insights into the 2024 Seismic Swarms on the Ionian Side of the Calabrian Arc
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A New Catalogue and Insights into the 2022 Adriatic Offshore Seismic Sequence Using a Machine Learning-Based Procedure
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