Enhanced Supervised Descent Learning Technique for Electromagnetic Inverse Scattering Problems by the Deep Convolutional Neural Networks-Reference-Cited by-同舟云学术

Enhanced Supervised Descent Learning Technique for Electromagnetic Inverse Scattering Problems by the Deep Convolutional Neural Networks

Published:2022-08 Issue:8 Volume:70 Page:6195-6206
ISSN:0018-926X
Container-title:IEEE Transactions on Antennas and Propagation
language:
Short-container-title:IEEE Trans. Antennas Propagat.

Author:

Yao He Ming¹^ORCID,Guo Rui²^ORCID,Li Maokun²^ORCID,Jiang Lijun³^ORCID,Ng Michael Kwok Po¹

Affiliation:

1. Department of Mathematics, The University of Hong Kong, Pokfulam, Hong Kong

2. Department of Electronic Engineering, State Key Laboratory on Microwave and Digital Communications, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China

3. Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong

Funder

Research Grants Council of Hong Kong

Asian Office of Aerospace Research and Development

Hong Kong UGC

National Science Foundation of China

National Key Research and Development Program of China

Guangzhou Municipal Science and Technology Project

Beijing Innovation Center for Future Chip

Research Institute of Tsinghua, Pearl River Delta

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/8/9882001/09857755.pdf?arnumber=9857755

Reference51 articles.

1. Far-field subwavelength imaging with near-field resonant metalens scanning at microwave frequencies

2. Spectral Imaging of Individual Split-Ring Resonators

3. DeepNIS: Deep Neural Network for Nonlinear Electromagnetic Inverse Scattering

4. Enhanced Deep Learning Approach Based on the Deep Convolutional Encoder–Decoder Architecture for Electromagnetic Inverse Scattering Problems

5. DNNs as Applied to Electromagnetics, Antennas, and Propagation—A Review

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