The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Convolutional neural network for earthquake detection and location
Open accessAbstract
ConvNetQuake is the first neural network for detection and location of earthquakes from seismograms.
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Citations
Cites
ImageNet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155
Adam: A Method for Stochastic Optimization
Kingma, D. P., & Ba, J. (2014) · arXiv · doi:10.48550/arxiv.1412.6980 · Cited by 98,946
LeCun, Y., Bengio, Y., & Hinton, G. (2015) · Nature · doi:10.1038/nature14539 · Cited by 84,126
WaveNet: a generative model for raw audio
Oord, A. V. D., Dieleman, S., Zen, H., Simonyan, K., Vinyals, O., Graves, A., Kalchbrenner, N., Senior, A., & Kavukcuoglu, K. (2016) · arXiv · doi:10.48550/arxiv.1609.03499 · Cited by 4,911
Feature selection, L 1 vs. L 2 regularization, and rotational invariance
Ng, A. Y. (2004) · Twenty-first international conference on Machine learning - ICML '04 · doi:10.1145/1015330.1015435 · Cited by 1,572
Data Augmentation for Deep Neural Network Acoustic Modeling
Cui, X., Goel, V., & Kingsbury, B. (2015) · IEEE/ACM Transactions on Audio, Speech, and Language Processing · doi:10.1109/taslp.2015.2438544 · Cited by 376
The microsoft 2016 conversational speech recognition system
Xiong, W., Droppo, J., Huang, X., Seide, F., Seltzer, M., Stolcke, A., Yu, D., & Zweig, G. (2017) · 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) · doi:10.1109/icassp.2017.7953159 · Cited by 326
Cited by
Machine learning for data-driven discovery in solid Earth geoscience
Bergen, K. J., Johnson, P. A., de Hoop, M. V., & Beroza, G. C. (2019) · Science · doi:10.1126/science.aau0323 · Cited by 1,249
Generalized Seismic Phase Detection with Deep Learning
Ross, Z. E., Meier, M., Hauksson, E., & Heaton, T. H. (2018) · Bulletin of the Seismological Society of America · doi:10.1785/0120180080 · Cited by 532
Applications of artificial intelligence for disaster management
Sun, W., Bocchini, P., & Davison, B. D. (2020) · Natural Hazards · doi:10.1007/s11069-020-04124-3 · Cited by 491
Deep learning and its application in geochemical mapping
Zuo, R., Xiong, Y., Wang, J., & Carranza, E. J. M. (2019) · Earth-Science Reviews · doi:10.1016/j.earscirev.2019.02.023 · Cited by 426
Li, W., & Hsu, C.-Y. (2022) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi11070385 · Cited by 147
Metadata
- Authors
- Perol, T., Gharbi, M., & Denolle, M.
- Venue
- Science Advances
- Published
- 2018-02-02
- Volume
- 4
- Issue
- 2
- Pages
- e1700578-e1700578
- ISSN
- 2375-2548 (ISSN-L)
- OpenAlex
- W2762410434
- Cited by
- 921
- References
- 7
- FWCI
- 51.49
- Type
- journal article
- Language
- en
- Open access
- gold
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- Perol, T., Gharbi, M., & Denolle, M. (2018). Convolutional neural network for earthquake detection and location. Science Advances. https://doi.org/10.1126/sciadv.1700578
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
