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Yews is an open-source project dedicated to provide a deep learning framework for processing seismological data. It provides abstract classes for deep learning tasks as well as automation tools for preparing seismic dataset.
[April 12 2019] We have a logo now.
We held our first internal workshop to introduce the Yews package and open for internal alpha test.
- Processing seismic waveform data by deep learning
- Peripheral tools to facilitate deep learning research in seismic processing
- Release an alpha test version (0.0.1) in April 2019
- Release beta test version (tentatively v0.0.5) in August 2019
- Release the first stable version (v0.1.0) in December 2019
- Prepare release to package managers including pip and conda (0.0.1)
- Setup Travis CI and codecov
- Include unittest via pytest
- Start online documentation via sphinx
- Get a list of feature request from EAS scholars
Please support the project by acknowledging the use of it. This helps us keep it alive. If you use Yews for work resulting in an academic publication, we would be grateful if one of the following papers is cited:
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Zhu, L., Peng, Z., McClellan, J., Li, C., Yao, D., Li, Z., & Fang, L. (2019).
Deep learning for seismic phase detection and picking in the aftershock zone of 2008 Mw7. 9 Wenchuan.
arXiv preprint
arXiv:1901.06396. -
Zhu, L., Peng, Z., & McClellan, J. (2018, October).
Deep learning for seismic event detection of earthquake aftershocks.
In 2018 52nd Asilomar Conference on Signals, Systems, and Computers (pp. 1121-1125). IEEE.
DOI: 10.1109/ACSSC.2018.8645360 -
Zhu, L., Peng, Z., & McClellan, J. (2018, June).
Event Detection and Phase Picking Based on Deep Convolutional Neural Networks.
In 80th EAGE Conference and Exhibition 2018.
DOI: 10.3997/2214-4609.201801052 -
Zhu, L., Li, Z., Li, C., Wang, B., Chen, Z., McClellan, J. H., & Peng, Z. (2017, December).
Machine-Learning Inspired Seismic Phase Detection for Aftershocks of the 2008 MW7. 9 Wenchuan Earthquake.
In AGU Fall Meeting Abstracts, 2017.
