Physics-informed neural networks for inverse problems in nano-optics and metamaterials
In this paper, we employ the emerging paradigm of physics-informed neural networks
(PINNs) for the solution of representative inverse scattering problems in photonic …
(PINNs) for the solution of representative inverse scattering problems in photonic …
Deep-learning schemes for full-wave nonlinear inverse scattering problems
This paper is devoted to solving a full-wave inverse scattering problem (ISP), which is aimed
at retrieving permittivities of dielectric scatterers from the knowledge of measured scattering …
at retrieving permittivities of dielectric scatterers from the knowledge of measured scattering …
A review on fast tomographic imaging techniques and their potential application in industrial process control
With the ongoing digitalization of industry, imaging sensors are becoming increasingly
important for industrial process control. In addition to direct imaging techniques such as …
important for industrial process control. In addition to direct imaging techniques such as …
DeepNIS: Deep neural network for nonlinear electromagnetic inverse scattering
L Li, LG Wang, FL Teixeira, C Liu… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Nonlinear electromagnetic (EM) inverse scattering is a quantitative and super-resolution
imaging technique, in which more realistic interactions between the internal structure of …
imaging technique, in which more realistic interactions between the internal structure of …
A low cost and portable microwave imaging system for breast tumor detection using UWB directional antenna array
Globally, breast cancer is a major reason for female mortality. Due to the limitations of
current clinical imaging, the researchers are encouraged to explore alternative and …
current clinical imaging, the researchers are encouraged to explore alternative and …
Physics-inspired convolutional neural network for solving full-wave inverse scattering problems
In this paper, to bridge the gap between physical knowledge and learning approaches, we
propose an induced current learning method (ICLM) by incorporating merits in traditional …
propose an induced current learning method (ICLM) by incorporating merits in traditional …
A plug-and-play priors approach for solving nonlinear imaging inverse problems
US Kamilov, H Mansour… - IEEE Signal Processing …, 2017 - ieeexplore.ieee.org
In the past two decades, nonlinear image reconstruction methods have led to substantial
improvements in the capabilities of numerous imaging systems. Such methods are …
improvements in the capabilities of numerous imaging systems. Such methods are …
Microwave imaging by means of Lebesgue-space inversion: An overview
An overview of the recent advancements in the development of microwave imaging
procedures based on the exploitation of the regularization theory in Lebesgue spaces is …
procedures based on the exploitation of the regularization theory in Lebesgue spaces is …
Deep learning-based inversion methods for solving inverse scattering problems with phaseless data
Without phase information of the measured field data, the phaseless data inverse scattering
problems (PD-ISPs) counter more serious nonlinearity and ill-posedness compared with full …
problems (PD-ISPs) counter more serious nonlinearity and ill-posedness compared with full …
Physics embedded deep neural network for solving full-wave inverse scattering problems
In this work, we design an iterative deep neural network to solve full-wave inverse scattering
problems (ISPs) in the 2-D case. Forward modeling neural networks that predict the …
problems (ISPs) in the 2-D case. Forward modeling neural networks that predict the …