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...

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Bibliographic Details
Main Authors: Shaofei Zang, Yuhu Cheng, Xuesong Wang, Qiang Yu, Guo-Sen Xie
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9149905/