Electromagnetic Imaging for Buried Conductors Using Deep Convolutional Neural Networks
In the past, many conventional algorithms, such as self-adaptive dynamic differential evolution and asynchronous particle swarm optimization, were used to reconstruct buried objects in the frequency domain; these were unfortunately time-consuming during the iterative, repeated computing process of t...
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| Principais autores: | , , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado: |
MDPI AG
2023-06-01
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| Series: | Applied Sciences |
| Assuntos: | |
| Acceso en liña: | https://www.mdpi.com/2076-3417/13/11/6794 |
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