基于物理增强神经网络的连续太赫兹波同轴数字全息成像
Article Properties
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LanguageEnglish
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DOI (url)
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Publication Date2023/01/01
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Journal
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Indian UGC (journal)
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Refrences35
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赵洁 Zhao Jie
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金晓宇 Jin Xiaoyu
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王大勇 Wang Dayong
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戎路 Rong Lu
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王云新 Wang Yunxin
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林述锋 Lin Shufeng
Cite
Zhao Jie 赵洁, et al. “基于物理增强神经网络的连续太赫兹波同轴数字全息成像”. Laser &Amp; Optoelectronics Progress, vol. 60, no. 18, 2023, p. 1811002, https://doi.org/10.3788/lop231397.
Zhao Jie 赵., Jin Xiaoyu 金., Wang Dayong 王., Rong Lu 戎., Wang Yunxin 王., & Lin Shufeng 林. (2023). 基于物理增强神经网络的连续太赫兹波同轴数字全息成像. Laser &Amp; Optoelectronics Progress, 60(18), 1811002. https://doi.org/10.3788/lop231397
Zhao Jie 赵洁, Jin Xiaoyu 金晓宇, Wang Dayong 王大勇, Rong Lu 戎路, Wang Yunxin 王云新, and Lin Shufeng 林述锋. “基于物理增强神经网络的连续太赫兹波同轴数字全息成像”. Laser &Amp; Optoelectronics Progress 60, no. 18 (2023): 1811002. https://doi.org/10.3788/lop231397.
1.
Zhao Jie 赵, Jin Xiaoyu 金, Wang Dayong 王, Rong Lu 戎, Wang Yunxin 王, Lin Shufeng 林. 基于物理增强神经网络的连续太赫兹波同轴数字全息成像. Laser & Optoelectronics Progress. 2023;60(18):1811002.
Journal Categories
Science
Physics
Optics
Light
Technology
Electrical engineering
Electronics
Nuclear engineering
Electric apparatus and materials
Electric circuits
Electric networks
Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| 深度学习用于连续太赫兹同轴数字全息重建 | Chinese Journal of Lasers |
| 2023 | |
Research on terahertz real-time near-field spectral imaging | Acta Physica Sinica |
| 5 | 2022 |
| Research on terahertz real-time near-field spectral imaging | Acta Physica Sinica |
| 5 | 2022 |
| 深度学习在数字全息显微成像中的应用 | Laser & Optoelectronics Progress |
| 4 | 2021 |
| Terahertz image super-resolution based on a complex convolutional neural network | 2021 |
Refrences Analysis
The category
Science: Physics: Optics. Light 6
is the most frequently represented among the references in this article. It primarily includes studies from Applied Sciences and NDT & E International. The chart below illustrates the number of referenced publications per year.