Explain image classifier by showing features in source and target domains with XSDA-Net
Explain image classifier by showing features in source and target domains with XSDA-Net
Explainable Supervised Domain Adaptation
arXiv paper abstract https://arxiv.org/abs/2205.09943
arXiv PDF paper https://arxiv.org/pdf/2205.09943v1.pdf
Domain adaptation techniques have contributed to the success of deep learning.
Leveraging knowledge from an auxiliary source domain for learning in labeled data-scarce target domain is fundamental to domain adaptation.
... While ... techniques result in increasing accuracy ... knowledge leveraged from the source domain, remains unclear.
... proposes an explainable by design supervised domain adaptation framework - XSDA-Net.
... mechanism into the XSDA-Net to explain the prediction of a test instance in terms of similar-looking regions in the source and target train images.
... demonstrate the utility of ... framework by curating the domain adaptation settings on datasets ... known to exhibit part-based explainability.
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