Name
Abstract | ||
|---|---|---|
Semantic segmentation of remote sensing images plays an important role in many applications. However, a remote sensing image typically comprises a complex and heterogenous urban landscape with objects in various sizes and materials, which causes challenges to the task. In this work, a novel adaptive fusion network (AFNet) is proposed to improve the performance of very high resolution (VHR) remote ... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TGRS.2020.3034123 | IEEE Transactions on Geoscience and Remote Sensing |
Keywords | DocType | Volume |
Image segmentation,Simultaneous localization and mapping,Adaptive systems,Semantics,Optical imaging,Labeling,Convolutional neural networks | Journal | 59 |
Issue | ISSN | Citations |
9 | 0196-2892 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rui Liu | 1 | 0 | 0.34 |
| Li Mi | 2 | 1 | 1.02 |
| Zhenzhong Chen | 3 | 1244 | 101.41 |