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...
Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-06-01
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Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/13/11/6794 |