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Automated design of a convolutional neural network with multi-scale filters for cost-efficient seismic data classification
Geoscientists mainly identify subsurface geologic features using exploration-derived seismic data. Classification or segmentation of 2D/3D seismic images commonly relies on conventional deep learning methods for image recognition. However, complex reflections of seismic waves tend to form high-dimen...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Nature Publishing Group UK
2020
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7335201/ https://www.ncbi.nlm.nih.gov/pubmed/32620867 http://dx.doi.org/10.1038/s41467-020-17123-6 |