Name
Abstract | ||
|---|---|---|
To boost the object grabbing capability of underwater robots for open-sea farming, we propose a new dataset (UDD) consisting of three categories (seacucumber, seaurchin, and scallop) with 2,227 images. To the best of our knowledge, it is the first 4K HD dataset collected in a real open-sea farm. We also propose a novel Poisson-blending Generative Adversarial Network (Poisson GAN) and an efficient ... |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/TCSVT.2021.3100059 | IEEE Transactions on Circuits and Systems for Video Technology |
Keywords | DocType | Volume |
Object detection,Generative adversarial networks,Detectors,Robots,Unmanned underwater vehicles,Training,Target tracking | Journal | 32 |
Issue | ISSN | Citations |
5 | 1051-8215 | 0 |
PageRank | References | Authors |
0.34 | 0 | 9 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chongwei Liu | 1 | 0 | 0.68 |
| Zhihui Wang | 2 | 19 | 7.84 |
| Shijie Wang | 3 | 0 | 0.34 |
| Tao Tang | 4 | 664 | 78.90 |
| Yulong Tao | 5 | 1 | 1.36 |
| Caifei Yang | 6 | 3 | 1.07 |
| Haojie Li | 7 | 1427 | 65.70 |
| Xing Liu | 8 | 3 | 1.07 |
| Xin Fan | 9 | 776 | 104.55 |