Name
Title | ||
|---|---|---|
Classification of PolSAR Images Based on Adaptive Nonlocal Stacked Sparse Autoencoder. |
Abstract | ||
|---|---|---|
Land cover classification using polarimetric synthetic aperture radar (PolSAR) images is an important tool for remote sensing analysis. In view that PolSAR image effective interpretation is commonly affected by the absence of discriminative features and the presence of speckle noises, this letter proposes an adaptive nonlocal stacked sparse autoencoder (ANSSAE) to achieve PolSAR image classificati... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/LGRS.2018.2829182 | IEEE Geoscience and Remote Sensing Letters |
Keywords | Field | DocType |
Speckle,Feature extraction,Covariance matrices,Robustness,Linear programming,Synthetic aperture radar,Fans | Computer vision,Autoencoder,Speckle pattern,Synthetic aperture radar,Robustness (computer science),Feature extraction,Pixel,Artificial intelligence,Contextual image classification,Discriminative model,Mathematics | Journal |
Volume | Issue | ISSN |
15 | 7 | 1545-598X |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuanyuan Hu | 1 | 0 | 1.01 |
| Jianchao Fan | 2 | 186 | 15.72 |
| Jun Wang | 3 | 9228 | 736.82 |