Push the Generalization Limitation of Learning Approaches by Multidomain Weight-Sharing for Full-Wave Inverse Scattering-Reference-Cited by-同舟云学术

Push the Generalization Limitation of Learning Approaches by Multidomain Weight-Sharing for Full-Wave Inverse Scattering

Published:2023 Issue: Volume:61 Page:1-14
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Wang Yusong¹^ORCID,Zong Zheng¹^ORCID,He Siyuan¹^ORCID,Song Rencheng²^ORCID,Wei Zhun¹^ORCID

Affiliation:

1. College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China

2. Department of Biomedical Engineering and the Anhui Province Key Laboratory of Measuring Theory and Precision Instrument, Hefei University of Technology, Hefei, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Zhejiang Provincial Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10006360/10214143.pdf?arnumber=10214143

Reference51 articles.

1. Contrast Source Inversion Method: State of Art

2. Beyond the Born and Rytov approximations: A nonlinear approach to electromagnetic scattering

3. Subspace-Based Optimization Method for Solving Inverse-Scattering Problems

4. Adaptively Regularized Bases-Expansion Subspace Optimization Methods for Electrical Impedance Tomography

5. Inverse-scattering theory within the Rytov approximation

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