{"url":"/dataset/southern-california-seismic-network-data","name":"Southern California Seismic Network Data","full_name":"Generalized Seismic Phase Detection with Deep Learning","description_markdown":"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).","description_withheld":null,"homepage":"https://scedc.caltech.edu/data/deeplearning.html#phase_detection","introduced_date":"2019-01-11","introduced_date_note":null,"introduced_by":{"paper":"/paper/generalized-seismic-phase-detection-with-deep","title":"Generalized Seismic Phase Detection with Deep Learning","first_author":null,"url":null},"license":null,"modalities":[],"tasks":[{"name":"Seismic Detection","url":"/task/seismic-detection","datasets_with_task":"/datasets/task/seismic-detection"}],"languages":[],"variants":["Southern California Seismic Network Data"],"data_loaders":[],"num_papers_in_archive":3,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/seismic-detection-on-southern-california","task":"Seismic Detection","dataset_variant":"Southern California Seismic Network Data","rows":2,"metrics":["Top-1 accuracy %"],"first_row_in_archive_order":{"model":"Seismo-Performer","paper":"/paper/the-seismo-performer-a-novel-machine-learning","metrics":{"Top-1 accuracy %":"98.71"},"code_links":[{"title":"jamm1985/seismo-performer","url":"https://github.com/jamm1985/seismo-performer"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/the-seismo-performer-a-novel-machine-learning","title":"The Seismo-Performer: A Novel Machine Learning Approach for General and Efficient Seismic Phase Recognition from Local Earthquakes in Real Time","date":"2021-09-19","rows_on_this_dataset":2,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}