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Abstract: While deep learning techniques have shown promising performance in the Major Depressive Disorder (MDD) detection task, they still face limitations in real-world scenarios. Specifically, ...

Abstract: We study source-free unsupervised domain adaptation (SFUDA) for semantic segmentation, which aims to adapt a source-trained model to the target domain without accessing the source data. Many ...

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The main challenge for Source-free Universal Domain Adaptation (SF-UniDA) is determining whether covariate-shifted samples belong to target-private unknown categories. Existing methods tackle this ...