Special Issue: Machine Learning for Electromagnetic Sensing and Imaging

Editors: Zhun Wei Feng Xu Xudong Chen Massimo Panella

2021-01-01

Special Issue Information

This Special Issue aims to invite researchers to contribute original research papers, dealing with all aspects of machine learning in electromagnetics. Topics of interest include, but are not limited to:

• Machine learning for remote sensing
• Machine learning for electromagnetic imaging
• Machine learning for electromagnetic inverse design
• Electromagnetic intelligent sensing

Special Issue Editors:

Zhun Wei

Zhejiang University
China

Feng Xu

University of Shanghai for Science and Technology
China

Xudong Chen

National University of Singapore
Singapore, 117576

Massimo Panella

Univ Roma La Sapienza
Italy

Manuscipts Submission:

Manuscripts should be submitted online. This special issue title should be selected during the online submission process. All papers will be peer-reviewed. Accepted papers will be published online continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers).

Published Papers in This Special Issue:

2020-06-29

A Review of Deep Learning Approaches for Inverse Scattering Problems (Invited Review)

By Xudong Chen, Zhun Wei, Maokun Li and Paolo Rocca.

Progress In Electromagnetics Research, Vol. 167, 67-81, 2020

doi: 10.2528/PIER20030705

2021-12-31

Recent Advances in Transfer Function-Based Surrogate Optimization for EM Design (Invited)

By Wei Liu, Feng Feng and Qijun Zhang.

Progress In Electromagnetics Research, Vol. 172, 61-75, 2021

doi: 10.2528/PIER21110302

2022-07-05

A Fast Deep Learning Technique for Wi-Fi-Based Human Activity Recognition

By Federico Succetti, Antonello Rosato, Francesco Di Luzio, Andrea Ceschini and Massimo Panella.

Progress In Electromagnetics Research, Vol. 174, 127-141, 2022

doi: 10.2528/PIER22042605

2022-07-14

Machine-Learning-Enabled Recovery of Prior Information from Experimental Breast Microwave Imaging Data

By Keeley Edwards, Joe LoVetri, Colin Gilmore and Ian Jeffrey.

Progress In Electromagnetics Research, Vol. 175, 1-11, 2022

doi: 10.2528/PIER22051601

2022-08-09

Machine Learning-Assisted Sensing Techniques for Integrated Communications and Sensing in WLANs : Current Status and Future Directions

By Siyuan Shao, Min Fan, Cheng Yu, Yan Li, Xiaodong Xu and Haiming Wang.

Progress In Electromagnetics Research, Vol. 175, 45-79, 2022

doi: 10.2528/PIER22042903

2022-11-26

Optical Neural Networks for Holographic Image Recognition (Invited Paper)

By Yiming Feng, Junru Niu, Yiyun Zhang, Yixuan Li, Hongsheng Chen and Haoliang Qian.

Progress In Electromagnetics Research, Vol. 176, 25-33, 2023

doi: 10.2528/PIER22092907

2023-12-08

Generalized Phase Retrieval Model Based on Physics-Inspired Network for Holographic Metasurface (Invited Paper)

By Lei Jin, Jialei Xie, Baicao Pan and Guoqing Luo.

Progress In Electromagnetics Research, Vol. 178, 103-110, 2023

doi: 10.2528/PIER23100604