An Early Fusion Deep Learning Framework for Solving Electromagnetic Inverse Scattering Problems
Y Wang, Y Zhao, L Wu, X Yin, H Zhou… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
This article presents a novel early fusion framework (EFF) of deep learning (DL) for solving
electromagnetic (EM) inverse-scattering problems (ISPs) in real time with high accuracy. The …
electromagnetic (EM) inverse-scattering problems (ISPs) in real time with high accuracy. The …
An Enhanced Diffractive Neural Network for Metasurface Holograms with High Resolution, Low Noise, and Uniform Intensity
M Qu, K Zhang, J Su, Y Li, L Deng… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
In this article, an enhanced diffractive neural network is proposed for achieving metasurface
holograms with high resolution, low noise, and uniform intensity. First, we prove the …
holograms with high resolution, low noise, and uniform intensity. First, we prove the …
Inhomogeneous Media Inverse Scattering Problem Assisted by Swin Transformer Network
A deep learning-assisted inversion method is proposed to solve the inhomogeneous
background imaging problem. First, a noniterative method called the distorted-Born modified …
background imaging problem. First, a noniterative method called the distorted-Born modified …
Contrast source inversion of sparse targets through multi-resolution Bayesian compressive sensing
The retrieval of non-Born scatterers is addressed within the contrast source inversion (CSI)
framework by means of a novel multi-step inverse scattering method that jointly exploits prior …
framework by means of a novel multi-step inverse scattering method that jointly exploits prior …
Physics Embedded Weight-Sharing Neural Network for Electrical Impedance Tomography
In this work, we present a physics-embedded deep neural network for 2D electrical
impedance tomography (EIT), which unfolds the supervised descent method with cascaded …
impedance tomography (EIT), which unfolds the supervised descent method with cascaded …