Two-step enhanced deep learning approach for electromagnetic inverse scattering problems
In this letter, a new deep learning (DL) approach is proposed to solve the electromagnetic
inverse scattering (EMIS) problems. The conventional methods for solving inverse problems …
inverse scattering (EMIS) problems. The conventional methods for solving inverse problems …
Compressive sensing as applied to inverse problems for imaging: theory, applications, current trends, and open challenges
Compressive sensing (CS) is currently one the most active research fields in information
engineering and science. The flexibility, robustness, accuracy, effectiveness, and sound …
engineering and science. The flexibility, robustness, accuracy, effectiveness, and sound …
Full-waveform inversion of crosshole radar data based on 2-D finite-difference time-domain solutions of Maxwell's equations
Crosshole radar techniques are important tools for a wide range of geoscientific and
engineering investigations. Unfortunately, the resolution of crosshole radar images may be …
engineering investigations. Unfortunately, the resolution of crosshole radar images may be …
Application of a new 2D time-domain full-waveform inversion scheme to crosshole radar data
Crosshole radar tomography is a useful tool in diverse investigations in geology,
hydrogeology, and engineering. Conventional tomograms provided by standard ray-based …
hydrogeology, and engineering. Conventional tomograms provided by standard ray-based …
Enhanced deep learning approach based on the deep convolutional encoder–decoder architecture for electromagnetic inverse scattering problems
This letter proposes a novel deep learning (DL) approach to resolve the electromagnetic
inverse scattering (EMIS) problems. The conventional approaches of resolving EMIS …
inverse scattering (EMIS) problems. The conventional approaches of resolving EMIS …
Enhanced two-step deep-learning approach for electromagnetic-inverse-scattering problems: Frequency extrapolation and scatterer reconstruction
The electromagnetic-inverse-scattering (EMIS) problem is solved by a novel two-step deep-
learning (DL) approach in this article. The newly proposed two-step DL approach not only …
learning (DL) approach in this article. The newly proposed two-step DL approach not only …
Enhanced supervised descent learning technique for electromagnetic inverse scattering problems by the deep convolutional neural networks
This work proposes a novel deep learning (DL) framework to solve the electromagnetic
inverse scattering (EMIS) problems. The proposed framework integrates the complex-valued …
inverse scattering (EMIS) problems. The proposed framework integrates the complex-valued …
A target shape estimation algorithm for pulse radar systems based on boundary scattering transform
T Sakamoto, T Sato - IEICE transactions on communications, 2004 - search.ieice.org
Environment measurement is an important issue for various applications including
household robots. Pulse radars are promising candidates in a near future. Estimating target …
household robots. Pulse radars are promising candidates in a near future. Estimating target …
Enhanced Deep Learning Approach Based on the Conditional Generative Adversarial Network for Electromagnetic Inverse Scattering Problems
This communication proposes a novel deep-learning (DL) framework for the electromagnetic
inverse scattering (EMIS) problems. Solving EMIS problems is a challenging topic due to …
inverse scattering (EMIS) problems. Solving EMIS problems is a challenging topic due to …
Time-domain sensing of targets buried under a rough air-ground interface
T Dogaru, L Carin - IEEE Transactions on Antennas and …, 1998 - ieeexplore.ieee.org
We consider plane wave time-domain scattering from a fixed target in the presence of a
rough (random) surface with application to ground penetrating radar. The time-domain …
rough (random) surface with application to ground penetrating radar. The time-domain …