A multi-task self-supervised framework with spatial mix-up masking and contrastive predictive coding improves unsupervised domain adaptation for classifying multi-type point maps from cancer tissue regions.
Domain- adversarial training of neural networks.Journal of ma- chine learning research, 17(59):1–35, 2016
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Spatially-Delineated Domain-Adapted AI Classification: An Application for Oncology Data
A multi-task self-supervised framework with spatial mix-up masking and contrastive predictive coding improves unsupervised domain adaptation for classifying multi-type point maps from cancer tissue regions.