Southern California Earthquake Data Center

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Special Data Sets

Training and Validation Data Sets for Deep Learning

P Wave Picking and First Motion Polarity Generalized Phase Detection

 

P Wave Arrival Picking and First‐Motion Polarity Determination With Deep Learning

These files are supplemental material for "P Wave Arrival Picking and First‐Motion Polarity Determination With Deep Learning” doi.org/10.1029/2017JB015251. hdf5 files correspond to the training and validation data sets used in the paper. The trained model and model architecture are also included. For additional information, please contact Zachary Ross (zross@gps.caltech.edu).

 

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Generalized Seismic Phase Detection with Deep Learning

These files are supplementary material for “Generalized Seismic Phase Detection with Deep Learning” by Ross et al. (2018), BSSA (doi.org/10.1785/0120180080). The models were trained using keras and TensorFlow, and can be used with these libraries. The training dataset contains 4.5 million seismograms evenly split between P-waves, S-waves, and pre-event noise classes. We encourage the use of this hdf5 dataset for training deep learning models, and hope that it and the model architecture in the paper can serve as a benchmark for future studies. For additional information please contact Zachary Ross (zross@gps.caltech.edu).

 

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