Multiple labeling
RedBrick AI has comprehensive features to help you record multiple annotations per image. There are two core use cases for multiple labeling:
Consensus: Have multiple labelers annotate a single task and record their inter-annotator agreement scores, i.e., measure the overlap between their annotations. The output of consensus is a single set of ground truth.
Task duplication: Have multiple annotators annotate a single image and generate N unique ground truth records for a single image.
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