Siamese Earthquake Transformer: A Pair‐Input Deep‐Learning Model for Earthquake Detection and Phase Picking on a Seismic Array
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Siamese Earthquake Transformer: A Pair‐Input Deep‐Learning Model for Earthquake Detection and Phase Picking on a Seismic Array
Authors
Keywords
-
Journal
JOURNAL OF GEOPHYSICAL RESEARCH-SOLID EARTH
Volume 126, Issue 5, Pages -
Publisher
American Geophysical Union (AGU)
Online
2021-04-26
DOI
10.1029/2020jb021444
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Real-time determination of earthquake focal mechanism via deep learning
- (2021) Wenhuan Kuang et al. Nature Communications
- Subduction megathrust heterogeneity characterized from 3D seismic data
- (2020) James D. Kirkpatrick et al. Nature Geoscience
- Direct structural evidence of Indian continental subduction beneath Myanmar
- (2020) Tianyu Zheng et al. Nature Communications
- 3D fault architecture controls the dynamism of earthquake swarms
- (2020) Zachary E. Ross et al. SCIENCE
- Earthquake transformer—an attentive deep-learning model for simultaneous earthquake detection and phase picking
- (2020) S. Mostafa Mousavi et al. Nature Communications
- Pairwise Association of Seismic Arrivals with Convolutional Neural Networks
- (2019) Ian W. McBrearty et al. SEISMOLOGICAL RESEARCH LETTERS
- Deep learning for seismic phase detection and picking in the aftershock zone of 2008 M7.9 Wenchuan Earthquake
- (2019) Lijun Zhu et al. PHYSICS OF THE EARTH AND PLANETARY INTERIORS
- Searching for hidden earthquakes in Southern California
- (2019) Zachary E. Ross et al. SCIENCE
- Hybrid Event Detection and Phase‐Picking Algorithm Using Convolutional and Recurrent Neural Networks
- (2019) Yijian Zhou et al. SEISMOLOGICAL RESEARCH LETTERS
- Earthquakes track subduction fluids from slab source to mantle wedge sink
- (2019) Felix Halpaap et al. Science Advances
- CRED: A Deep Residual Network of Convolutional and Recurrent Units for Earthquake Signal Detection
- (2019) S. Mostafa Mousavi et al. Scientific Reports
- Seismic Phase Picking Using Convolutional Networks
- (2019) Esteban Pardo et al. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
- Rapid Earthquake Association and Location
- (2019) Miao Zhang et al. SEISMOLOGICAL RESEARCH LETTERS
- Unsupervised Clustering of Seismic Signals Using Deep Convolutional Autoencoders
- (2019) S. Mostafa Mousavi et al. IEEE Geoscience and Remote Sensing Letters
- Importance of later phases in seismic tomography
- (2019) Dapeng Zhao PHYSICS OF THE EARTH AND PLANETARY INTERIORS
- Beyond Correlation: A Path‐Invariant Measure for Seismogram Similarity
- (2019) Joshua Dickey et al. SEISMOLOGICAL RESEARCH LETTERS
- Lower-mantle plume beneath the Yellowstone hotspot revealed by core waves
- (2018) Peter L. Nelson et al. Nature Geoscience
- Deep visual tracking: Review and experimental comparison
- (2018) Peixia Li et al. PATTERN RECOGNITION
- Convolutional neural network for earthquake detection and location
- (2018) Thibaut Perol et al. Science Advances
- DeepDetect: A Cascaded Region-Based Densely Connected Network for Seismic Event Detection
- (2018) IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
- Holistically-Nested Edge Detection
- (2017) Saining Xie et al. INTERNATIONAL JOURNAL OF COMPUTER VISION
- Deep learning
- (2015) Yann LeCun et al. NATURE
- Waveform Relocated Earthquake Catalog for Southern California (1981 to June 2011)
- (2012) E. Hauksson et al. BULLETIN OF THE SEISMOLOGICAL SOCIETY OF AMERICA
- Migration of early aftershocks following the 2004 Parkfield earthquake
- (2009) Zhigang Peng et al. Nature Geoscience
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started