Active Gradual Domain Adaptation: Dataset and Approach
Published in IEEE Transaction on Multimedia, 2022
In this work, we proposed the active gradual self-training (AGST) algorithm with active pseudolabeling and gradual semi-supervised domain adaptation to adapt deep neural networks to the changing environments. We also created a new dataset – Evolving-Image-Search (EVIS).
Recommended citation: @ARTICLE{Zhou2021, author={Zhou, Shiji and Wang, Lianzhe and Zhang, Shanghang and Wang, Zhi and Zhu, Wenwu}, journal={IEEE Transactions on Multimedia}, title={Active Gradual Domain Adaptation: Dataset and Approach}, year={2022}, pages={1-1}, doi={10.1109/TMM.2022.3142524} } https://ieeexplore.ieee.org/document/9681347