Name
Title | ||
|---|---|---|
A Multiple Feature Fully Convolutional Network for Road Extraction From High-Resolution Remote Sensing Image Over Mountainous Areas |
Abstract | ||
|---|---|---|
Road extraction from the remote sensing image over mountainous areas is a difficult vision problem. In this letter, we propose a multiple feature fully convolutional network (MFFCN) on the basis of FCN for mountainous road extraction. The benefits of this model are twofold: first, MFFCN is a semantic segmentation model, which has deep convolutional networks. It avoids the problem of repeated stora... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/LGRS.2019.2905350 | IEEE Geoscience and Remote Sensing Letters |
Keywords | Field | DocType |
Feature extraction,Roads,Remote sensing,Deconvolution,Semantics,Image segmentation,Image resolution | Aster (genus),Computer vision,Segmentation,Remote sensing,Terrain,Deconvolution,Image segmentation,Feature extraction,Pixel,Artificial intelligence,Image resolution,Mathematics | Journal |
Volume | Issue | ISSN |
16 | 10 | 1545-598X |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yonghong Zhang | 1 | 7 | 3.89 |
| Guanghao Xia | 2 | 0 | 0.34 |
| Jiangeng Wang | 3 | 0 | 0.34 |
| Dron Lha | 4 | 0 | 0.34 |