Special Issue 2: Machine Learning for Electromagnetic Sensing and Imaging
Editors: Zhun Wei, Feng Xu, Xudong Chen and Massimo Panella

2020-12-14

◈ 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
Professor
Zhejiang University, China
Feng Xu
Professor
Fudan University, China
Xudong Chen
Professor
National University of Singapore, Singapore
Massimo Panella
Professor
University of Rome "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

More papers to be added here ...