Name
Title | ||
|---|---|---|
Unsupervised adversarial domain adaptation based on interpolation image for fish detection in aquaculture |
Abstract | ||
|---|---|---|
•An unsupervised adversarial domain adaptive model is proposed for fish detection.•Proposed method can improve robustness of cross-domain detection in aquaculture.•Interpolation samples fill the distribution gap between the different scenes.•The alignment of local and global features is realized by adversarial training.•Cross-domain experiments are performed to verify the method and prove its validity. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.compag.2022.107004 | Computers and Electronics in Agriculture |
Keywords | DocType | Volume |
Aquaculture,Fish detection,Unsupervised adversarial domain adaptation,Domain-invariant features | Journal | 198 |
ISSN | Citations | PageRank |
0168-1699 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tengyun Zhao | 1 | 0 | 0.68 |
| Zhencai Shen | 2 | 0 | 0.34 |
| Hui Zou | 3 | 1 | 0.69 |
| Ping Zhong | 4 | 40 | 11.34 |
| Yingyi Chen | 5 | 59 | 16.06 |