Monte Carlo Sampling of Inverse Problems Based on a Squeeze-and-Excitation Convolutional Neural Network Applied to Ground-Penetrating Radar Crosshole Traveltime: A Numerical Simulation Study
Monte Carlo-based sampling methods (MCMC) can be used to solve inverse problems affecting ground penetrating radar (GPR) data. However, due to their high computational complexity, they have not been widely used in practical applications. This article uses neural network methods to replace the comput...
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| Päätekijät: | , , |
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| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
MDPI AG
2024-01-01
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| Sarja: | Applied Sciences |
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| Linkit: | https://www.mdpi.com/2076-3417/14/2/618 |
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