Name
Abstract | ||
|---|---|---|
The rapid development of remote sensing technology allows us to get images with high and very high resolution (VHR). VHR imagery scene classification has become an important and challenging problem. In this paper, we introduce a framework for VHR scene understanding. First, the pretrained visual geometry group network (VGG-Net) model is proposed as deep feature extractors to extract informative fe... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TGRS.2017.2700322 | IEEE Transactions on Geoscience and Remote Sensing |
Keywords | Field | DocType |
Feature extraction,Remote sensing,Image resolution,Visualization,Correlation,Principal component analysis,Machine learning | Data set,Feature fusion,Remote sensing,Artificial intelligence,Computer vision,Pattern recognition,Visualization,Discriminant correlation analysis,Feature extraction,Aerial image,Image resolution,Principal component analysis,Mathematics | Journal |
Volume | Issue | ISSN |
55 | 8 | 0196-2892 |
Citations | PageRank | References |
16 | 0.53 | 33 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Souleyman Chaib | 1 | 20 | 1.27 |
| Huan Liu | 2 | 18 | 2.27 |
| Yanfeng Gu | 3 | 742 | 55.56 |
| Hongxun Yao | 4 | 2485 | 156.65 |