Name
Title | ||
|---|---|---|
RetinaNet: A deep learning architecture to achieve a robust wake detector in SAR images |
Abstract | ||
|---|---|---|
With the specific aim of improving our Maritime Domain Awareness, satellite data enable a wide range of applications, including fisheries and pollution control, anti-piracy actions, and surveillance over coastal/protected regions. Among all the available data, the ones gathered by space-borne synthetic aperture radar (SAR) are attracting large interest thanks to their coverage and all-weather and ... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/RTSI50628.2021.9597297 | 2021 IEEE 6th International Forum on Research and Technology for Society and Industry (RTSI) |
Keywords | DocType | ISBN |
Deep learning,Sea surface,Satellites,Surveillance,Spaceborne radar,Detectors,Radar polarimetry | Conference | 978-1-6654-4135-3 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Roberto Del Prete | 1 | 0 | 0.34 |
| Maria Daniela Graziano | 2 | 8 | 6.37 |
| Alfredo Renga | 3 | 50 | 13.53 |