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Microwave Imaging by Deep Learning Network: Feasibility and Training Method
Microwave image reconstruction based on a deep-learning method is investigated in this paper. The neural network is capable of converting measured microwave signals acquired from a 24×24 antenna array at 4 GHz into a 128×128 image. To reduce the training difficulty, we first developed an autoencoder...
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| Vydáno v: | IEEE Trans Antennas Propag |
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| Hlavní autoři: | , |
| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
2020
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| Témata: | |
| On-line přístup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8189033/ https://ncbi.nlm.nih.gov/pubmed/34113046 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/tap.2020.2978952 |
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