Seismic Data Augmentation Based on Conditional Generative Adversarial Networks

Realistic synthetic data can be useful for data augmentation when training deep learning models to improve seismological detection and classification performance. In recent years, various deep learning techniques have been successfully applied in modern seismology. Due to the performance of deep lea...

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Detalles Bibliográficos
Autores principales: Li, Yuanming, Ku, Bonhwa, Zhang, Shou, Ahn, Jae-Kwang, Ko, Hanseok
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Letter
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7731344/
https://www.ncbi.nlm.nih.gov/pubmed/33266072
http://dx.doi.org/10.3390/s20236850

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7731344/
https://www.ncbi.nlm.nih.gov/pubmed/33266072
http://dx.doi.org/10.3390/s20236850

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