Name
Abstract | ||
|---|---|---|
In visual understandings, images taken from different cameras usually have different resolutions, illumination, poses, and background views that lead to domain shift. Besides labeling these data is an expensive operation. These problems lead to the need for unsupervised domain adaptation (UDA), in which training and testing data are not drawn from the same distribution, and labels are not availabl... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ICSIPA52582.2021.9576812 | 2021 IEEE International Conference on Signal and Image Processing Applications (ICSIPA) |
Keywords | DocType | ISBN |
unsupervised domain adaptation,dimensionality reduction,distribution discrepancy | Conference | 978-1-6654-3592-5 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| M. S. Rizal Samsudin | 1 | 0 | 0.34 |
| S. A. R. Abu-Bakar | 2 | 79 | 9.67 |
| Musa Mohd Mokji | 3 | 38 | 7.00 |