RB-C1000, a pipeline combining active learning and semi-supervised pseudo-labeling, achieves roughly 98.8% real/bogus classification accuracy on new ZTF datasets using only 1,000 labels.
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The classification of real and bogus transients using active learning and semi-supervised learning
RB-C1000, a pipeline combining active learning and semi-supervised pseudo-labeling, achieves roughly 98.8% real/bogus classification accuracy on new ZTF datasets using only 1,000 labels.