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Active Semi-Supervised Learning by Exploring Per-Sample Uncertainty and Consistency
Active Learning (AL) and Semi-supervised Learning are two techniques that have been studied to reduce the high cost of deep learning by using a small amount of labeled data and a large amount of unlabeled data.
Pose-MUM : Reinforcing Key Points Relationship for Semi-Supervised Human Pose Estimation
A well-designed strong-weak augmentation strategy and the stable teacher to generate reliable pseudo labels are essential in the teacher-student framework of semi-supervised learning (SSL).
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