In recent years, deep learning (DL) is becoming an increasingly important tool for solving
inverse scattering problems (ISPs). This paper reviews methods, promises, and pitfalls of …

Objective: As a newly developed technique, focused microwave breast hyperthermia
(FMBH) can provide accurate and cost-effective treatment of breast tumors with low side …

In this article, an unrolling algorithm of the iterative subspace-based optimization method
(SOM) is proposed for solving full-wave inverse scattering problems (ISPs). The unrolling …

In this work, we present a deep-learning-based low-frequency (LF) data prediction scheme
to solve the highly nonlinear inverse scattering problem (ISP) with strong scatterers. The …

This study presents a deep learning based methodology for both remote sensing and design
of acoustic scatterers. The ability to determine the shape of a scatterer, either in the context …

Recently, deep learning methods have attracted intensive attentions on solving inverse
scattering problems (ISPs). However, different with traditional physical-model-based …

This article studies the full-wave electromagnetic inverse scattering (EMIS) problem that
aims to retrieve the permittivities of dielectric scatterers based on the knowledge of …

Perfect electric conductors (PECs) are reconstructed integrating the subspace-based
optimization method (SOM) within the iterative multiscaling approach (IMSA). Without a priori …

In this article, we have improved the quantitative inversion performance of the cross-
correlated contrast source inversion (CC-CSI) method by incorporating the subspace …

The phase information's role in deep neural networks (DNNs) to solve the electromagnetic
inverse scattering problems is investigated. The feedforward neutral network model with …