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Jul, 2023
PseudoCal: 基于无源方法的领域自适应非监督不确定性校准
PseudoCal: A Source-Free Approach to Unsupervised Uncertainty Calibration in Domain Adaptation
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Dapeng Hu, Jian Liang, Xinchao Wang, Chuan-Sheng Foo
TL;DR
本文提出了一种基于无标注目标数据的源自由校准方法PseudoCal,该方法解决了无标签目标域数据中目标领域内部不确定性的问题,并在10个UDA方法上展现了出色的校准效果。
Abstract
unsupervised domain adaptation
(UDA) has witnessed remarkable advancements in improving the accuracy of models for unlabeled target domains. However, the
calibration
of
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