Jamal, Muhammad Abdullah, Brown, Matthew, Yang, Ming-Hsuan, Wang, Liqiang, and Gong, Boqing. Rethinking Class-Balanced Methods for Long-Tailed Visual Recognition From a Domain Adaptation Perspective. Retrieved from https://par.nsf.gov/biblio/10204106. 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) . Web. doi:10.1109/CVPR42600.2020.00763.
Jamal, Muhammad Abdullah, Brown, Matthew, Yang, Ming-Hsuan, Wang, Liqiang, and Gong, Boqing.
"Rethinking Class-Balanced Methods for Long-Tailed Visual Recognition From a Domain Adaptation Perspective". 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (). Country unknown/Code not available. https://doi.org/10.1109/CVPR42600.2020.00763.https://par.nsf.gov/biblio/10204106.
@article{osti_10204106,
place = {Country unknown/Code not available},
title = {Rethinking Class-Balanced Methods for Long-Tailed Visual Recognition From a Domain Adaptation Perspective},
url = {https://par.nsf.gov/biblio/10204106},
DOI = {10.1109/CVPR42600.2020.00763},
abstractNote = {},
journal = {2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
author = {Jamal, Muhammad Abdullah and Brown, Matthew and Yang, Ming-Hsuan and Wang, Liqiang and Gong, Boqing},
editor = {null}
}
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