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.
Adversarial training on point clouds for sim-to-real 3d object detection.IEEE Robotics and Automation Letters, 6(4):6662–6669, 2021
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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.