Name
Title | ||
|---|---|---|
A New Deep Generative Network for Unsupervised Remote Sensing Single-Image Super-Resolution. |
Abstract | ||
|---|---|---|
Super-resolution (SR) brings an excellent opportunity to improve a wide range of different remote sensing applications. SR techniques are concerned about increasing the image resolution while providing finer spatial details than those captured by the original acquisition instrument. Therefore, SR techniques are particularly useful to cope with the increasing demand remote sensing imaging applicati... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TGRS.2018.2843525 | IEEE Transactions on Geoscience and Remote Sensing |
Keywords | Field | DocType |
Spatial resolution,Remote sensing,Image reconstruction,Data models,Imaging,Training | Iterative reconstruction,Data modeling,Computer vision,Normalization (statistics),Remote sensing,Remote sensing application,Artificial intelligence,Generative grammar,Upsampling,Image resolution,Superresolution,Mathematics | Journal |
Volume | Issue | ISSN |
56 | 11 | 0196-2892 |
Citations | PageRank | References |
6 | 0.40 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Juan Mario Haut | 1 | 54 | 5.33 |
| Rubén Fernández-Beltran | 2 | 51 | 10.18 |
| Mercedes Eugenia Paoletti | 3 | 41 | 3.33 |
| Antonio Plaza | 4 | 3475 | 262.63 |
| Antonio Plaza | 5 | 83 | 17.35 |
| Filiberto Pla | 6 | 24 | 1.64 |