Name
Title | ||
|---|---|---|
Glacier classification from Sentinel-2 imagery using spatial-spectral attention convolutional model |
Abstract | ||
|---|---|---|
•A novel spatial-spectral attention module with UNet architecture (SSUNet) was proposed.•SSUNet built an interdependencies between spatial-spectral domains via adaptively recalibrating the weighs of spatial-spectral features for each pixel.•SSUNet had strong generalization ability and improve the good performance for glacier mapping.•The study provided a timely and important supplementary to large-scale crop mapping. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.jag.2021.102445 | International Journal of Applied Earth Observation and Geoinformation |
Keywords | DocType | Volume |
Glacier classification,Sentinel-2,Spectral signal,Spatial correlation effect,Deep learning | Journal | 102 |
ISSN | Citations | PageRank |
1569-8432 | 0 | 0.34 |
References | Authors | |
0 | 8 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shuai Yan | 1 | 2 | 0.77 |
| Linlin Xu | 2 | 0 | 0.34 |
| Guojiang Yu | 3 | 2 | 0.77 |
| Longshan Yang | 4 | 0 | 0.34 |
| Wenju Yun | 5 | 0 | 0.34 |
| Dehai Zhu | 6 | 0 | 1.35 |
| Sijing Ye | 7 | 0 | 1.01 |
| Xiaochuang Yao | 8 | 0 | 0.34 |