Name
Abstract | ||
|---|---|---|
Ocean front plays an important role in marine fishery production and biogeochemical cycling. This letter proposes a multiscale deep framework to meet the need for automatic ocean front detection and fine-grained location. The framework mainly focuses on bringing a well-trained deep learning model into front detection and location on the global satellite sea surface temperature image. First, a mult... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/LGRS.2018.2869647 | IEEE Geoscience and Remote Sensing Letters |
Keywords | Field | DocType |
Machine learning,Ocean temperature,Silicon,Image edge detection,Detectors | Computer vision,Satellite,Sea surface temperature,Remote sensing,Binary image,Scanner,Artificial intelligence,Deep learning,Detector,Brightness,Mathematics,Binary number | Journal |
Volume | Issue | ISSN |
16 | 2 | 1545-598X |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xin Sun | 1 | 51 | 10.45 |
| Changgang Wang | 2 | 0 | 0.34 |
| Junyu Dong | 3 | 99 | 23.43 |
| Estanislau Lima | 4 | 12 | 1.65 |
| Yuting Yang | 5 | 44 | 10.79 |