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.
Causes and consequences of spatial heterogeneity in ecosystem function
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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.