Name
Abstract | ||
|---|---|---|
•A novel domain adaptation technique called Adaptive Batch Normalization (AdaBN).•The effectiveness of AdaBN is validated for both single source and multi-source domain adaptation tasks.•Experiments on the cloud detection for remote sensing images demonstrate the effectiveness of AdaBN in practical use. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.patcog.2018.03.005 | Pattern Recognition |
Keywords | Field | DocType |
Domain adaptation,Batch normalization,Neural networks | Object detection,Normalization (statistics),Pattern recognition,Domain adaptation,Artificial intelligence,Deep learning,Contextual image classification,Deep neural networks,Mathematics,Machine learning | Journal |
Volume | Issue | ISSN |
80 | 1 | 0031-3203 |
Citations | PageRank | References |
23 | 0.98 | 33 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yanghao Li | 1 | 194 | 13.98 |
| Naiyan Wang | 2 | 1642 | 57.85 |
| Jianping Shi | 3 | 920 | 43.57 |
| Xiaodi Hou | 4 | 2069 | 72.53 |
| Jiaying Liu | 5 | 860 | 83.96 |