.png){kind=icon}
返回
Deep-Learning-Based Calibration in Contrast Source Inversion Based Microwave Subsurface Imaging
.png){kind=icon}
PRE
AI
DOI：10.1109/LGRS.2022.3169799.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
A deep-learning (DL)-based data calibration technique applied to quantitative microwave inverse-scattering analysis is presented. This technique aims at subsurface inspection for the buried object under a concrete road or soil. The inverse-scattering analysis provides a complex permittivity profile, which is useful for object identification such as air gap or water. Contrast source inversion (CSI) is one of the most promising inverse-scattering methods. This method is capable of avoiding the iterative use of highly computational forward solvers. However, when applied to the measured data, an appropriate calibration capable of converting measured data to simulation data is required. In this work, a DL-based calibration suitable for nonlinear inverse problems is proposed. Its efficiency is experimentally demonstrated using a concrete cylinder containing water with different salinities.
Keyword:
Calibration
Data models
Permittivity
Frequency measurement
Analytical models
Training
Time-domain analysis
Contrast source inversion (CSI)
deep-learning (DL)-based calibration
inverse scattering analysis
microwave quantitative imaging
期刊
IF:
16.4
论文数:
1.0W
被引数:
5.1K
机构
引用论文
分享收藏Chelating Agent‐Assisted‐Bi2WO6 Nanostructured Materials for Electron Transfer‐Driven Ultrafast Catalytic Reduction of Organic and Inorganic Contaminants螯合剂辅助Bi2WO6纳米结构材料用于电子转移驱动的有机和无机污染物超快催化还原.png)
ChemNanoMat
ChemNanoMatIF0
PREAI
分享收藏
Enhancement of antenna decoupling bandwidth by utilizing common and differential modes cancellation
PREAI
分享收藏Magnetic resonance imaging of resting OEF and CMRO2 using a generalized calibration model for hypercapnia and hyperoxiaNeuroImage
NeuroImageIF0
PREAI
分享收藏
查看更多内容