Name
Title | ||
|---|---|---|
An End-to-End Network for Remote Sensing Imagery Semantic Segmentation via Joint Pixel- and Representation-Level Domain Adaptation |
Abstract | ||
|---|---|---|
It requires pixel-by-pixel annotations to obtain sufficient training data in supervised remote sensing image segmentation, which is a quite time-consuming process. In recent years, a series of domain-adaptation methods was developed for image semantic segmentation. In general, these methods are trained on the source domain and then validated on the target domain to avoid labeling new data repeated... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/LGRS.2020.3010591 | IEEE Geoscience and Remote Sensing Letters |
Keywords | DocType | Volume |
Gallium nitride,Image segmentation,Semantics,Remote sensing,Feature extraction,Adaptation models,Training | Journal | 18 |
Issue | ISSN | Citations |
11 | 1545-598X | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lukui Shi | 1 | 11 | 4.33 |
| Ziyuan Wang | 2 | 0 | 0.68 |
| Bin Pan | 3 | 44 | 5.65 |
| Zhenwei Shi | 4 | 559 | 63.11 |