Name
Abstract | ||
|---|---|---|
This article addresses the problem of remote sensing image pan-sharpening from the perspective of generative adversarial learning. We propose a novel deep neural network-based method named pansharpening GAN (PSGAN). To the best of our knowledge, this is one of the first attempts at producing high-quality pan-sharpened images with generative adversarial networks (GANs). The PSGAN consists of two co... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TGRS.2020.3042974 | IEEE Transactions on Geoscience and Remote Sensing |
Keywords | DocType | Volume |
Generative adversarial networks,Generators,Neural networks,Computer architecture,Training,Spatial resolution,Data models | Journal | 59 |
Issue | ISSN | Citations |
12 | 0196-2892 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qingjie Liu | 1 | 92 | 18.60 |
| Huanyu Zhou | 2 | 0 | 0.34 |
| Qizhi Xu | 3 | 35 | 5.79 |
| Xiangyu Liu | 4 | 51 | 14.10 |
| Yunhong Wang | 5 | 3816 | 278.50 |