Semi-supervised transfer subspace for domain adaptation

作者：

Highlights：

• A new semi-supervised method for domain adaptation.

• Labeled and unlabeled data are exploited effectively.

• The method provides significant reduction of domain shift.

• The method is more effective than other state-of-the-art methods.

摘要

•A new semi-supervised method for domain adaptation.•Labeled and unlabeled data are exploited effectively.•The method provides significant reduction of domain shift.•The method is more effective than other state-of-the-art methods.

论文关键词：Cross-domain knowledge transfer,Cross-dataset classification,Dataset bias,Metric learning,Semi-supervised learning

论文评审过程：Received 16 November 2016, Revised 19 February 2017, Accepted 12 April 2017, Available online 18 April 2017, Version of Record 21 November 2017.

论文官网地址：https://doi.org/10.1016/j.patcog.2017.04.011