Cross Domain Mean Approximation for Unsupervised Domain Adaptation
Unsupervised Domain Adaptation (UDA) aims to leverage the knowledge from the labeled source domain to help the task of target domain with the unlabeled data. It is a key step for UDA to minimize the cross-domain distribution divergence. In this paper, we firstly propose a novel discrepancy metric, r...
Main Authors: | Shaofei Zang, Yuhu Cheng, Xuesong Wang, Qiang Yu, Guo-Sen Xie |
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Format: | Article |
Language: | English |
Published: |
IEEE
2020-01-01
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Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9149905/ |
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