Name
Title | ||
|---|---|---|
Random Neighbor Pixel-Block-Based Deep Recurrent Learning for Polarimetric SAR Image Classification |
Abstract | ||
|---|---|---|
Polarimetric synthetic aperture radar (PolSAR) image classification is an important part of SAR data interpretation and provides more intuitive and detailed SAR polarization information. To bridge the PolSAR data and applications, it is necessary to design a comprehensive PolSAR classification framework to achieve satisfactory results. The deep neural network (DNN) appears to be a solution for the... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TGRS.2020.3037209 | IEEE Transactions on Geoscience and Remote Sensing |
Keywords | DocType | Volume |
Feature extraction,Training,Covariance matrices,Matrix decomposition,Data mining,Scattering,Training data | Journal | 59 |
Issue | ISSN | Citations |
9 | 0196-2892 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jun Ni | 1 | 6 | 2.45 |
| Fan Zhang | 2 | 53 | 6.66 |
| Qiang Yin | 3 | 0 | 1.01 |
| Yongsheng Zhou | 4 | 3 | 5.19 |
| Heng-Chao Li | 5 | 343 | 40.03 |
| HONG Wen | 6 | 7 | 7.73 |