• Corpus ID: 239768926

Domain Adaptation for Rare Classes Augmented with Synthetic Samples

@article{Das2021DomainAF,
  title={Domain Adaptation for Rare Classes Augmented with Synthetic Samples},
  author={Tuhinanksu Das and Robert-Jan Bruintjes and Attila Lengyel and Jan C. van Gemert and Sara Beery},
  journal={ArXiv},
  year={2021},
  volume={abs/2110.12216}
}
To alleviate lower classification performance on rare classes in imbalanced datasets, a possible solution is to augment the underrepresented classes with synthetic samples. Domain adaptation can be incorporated in a classifier to decrease the domain discrepancy between real and synthetic samples. While domain adaptation is generally applied on completely synthetic source domains and real target domains, we explore how domain adaptation can be applied when only a single rare class is augmented… 
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