4 citations · 5 across the 7 of their papers we have counts for
4 papers · 1 filter
Structured Multi-Level-Set Inversion for 3-D Electromagnetic Inverse Scattering
Yutong Du, Zicheng Liu, Bo Qi +3
Many dielectric targets encountered in 3-D electromagnetic inverse scattering exhibit piecewise-homogeneous material distributions, which provide useful structural information for…
Fast Physics-Driven Untrained Network for Highly Nonlinear Inverse Scattering Problems
Yutong Du, Zicheng Liu, Yi Huang +4
Untrained neural networks (UNNs) offer high-fidelity electromagnetic inverse scattering reconstruction but are computationally limited by high-dimensional spatial-domain optimizati…
Contrast-Source-Based Physics-Driven Neural Network for Inverse Scattering Problems
Yutong Du, Zicheng Liu
Deep neural networks (DNNs) have recently been applied to inverse scattering problems (ISPs) due to their strong nonlinear mapping capabilities. However, supervised DNN solvers req…
Improved Physics-Driven Neural Network to Solve Inverse Scattering Problems
Yutong Du, Zicheng Liu, Bo Wu +5
This paper presents an improved physics-driven neural network (IPDNN) framework for solving electromagnetic inverse scattering problems (ISPs). A new Gaussian-localized oscillation…