Southern California Seismic Network Data (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@caltech.edu).