RedBrick AI has comprehensive features to help you record multiple annotations per image or conduct multi-reader studies. There are two core use cases for multiple labeling on RedBrick AI:Documentation Index
Fetch the complete documentation index at: https://docs.redbrickai.com/llms.txt
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- Consensus, or multi-reader, single output: 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, or multi-reader, multiple output: Have multiple labelers annotate a single image and generate N unique ground truth records for a single image.
