A New Approach for Solving Inverse Scattering Problems Based on Physics-informed Supervised Residual Learning-Reference-Cited by-同舟云学术

A New Approach for Solving Inverse Scattering Problems Based on Physics-informed Supervised Residual Learning

Published:2022-03-27 Issue: Volume: Page:
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Container-title:2022 16th European Conference on Antennas and Propagation (EuCAP)
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Author:

Shan Tao¹,Lin Zhichao¹,Song Xiaoqian²,Li Maokun¹,Yang Fan¹,Xu Shenheng¹

Affiliation:

1. Beijing National Research Center for Information Science and Technology, Tsinghua University,Department of Electronic Engineering,Beijing,China,100084

2. National Institute of Metrology,Beijing,China,100013

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9768880/9768883/09769555.pdf?arnumber=9769555

Reference11 articles.

1. Overview and Classification of Some Regularization Techniques for the Gauss-Newton Inversion Method Applied to Inverse Scattering Problems

2. Contrast Source Inversion Method: State of Art

3. Identity mappings in deep residual networks;he;European Conference on Computer Vision,2016

4. Supervised Descent Learning Technique for 2-D Microwave Imaging

5. Physics-Informed Supervised Residual Learning for Electromagnetic Modeling;shan;2021 International Applied Computational Electromagnetics Society (ACES-China) Symposium,2021

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