Name
Title | ||
|---|---|---|
Performance Analysis and Dynamic Evolution of Deep Convolutional Neural Network for Electromagnetic Inverse Scattering |
Abstract | ||
|---|---|---|
The solution of electromagnetic (EM) inverse scattering problems is hindered by challenges, such as ill-posedness, nonlinearity, and high computational costs. Recently, deep learning was shown to be a promising tool in addressing these challenges. In particular, it is possible to establish a connection between a deep convolutional neural network (CNN) and iterative solution methods of EM inverse s... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/LAWP.2019.2927543 | IEEE Antennas and Wireless Propagation Letters |
Keywords | DocType | Volume |
Inverse problems,Image reconstruction,Training,Iterative methods,Image quality,Convolutional neural nets,Computational efficiency | Journal | 18 |
Issue | ISSN | Citations |
11 | 1536-1225 | 0 |
PageRank | References | Authors |
0.34 | 6 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lianlin Li | 1 | 102 | 17.46 |
| Long Gang Wang | 2 | 3 | 1.11 |
| Fernando L. Teixeira | 3 | 97 | 16.97 |