Introduce human intelligence into your data preparation workflows

Human-in-the-Loop functions

At Dataloop, we know that AI is dependent on human input for feeding models with validated data. Using our human-in-the-loop plugins, you can create powerful deep learning pipelines that require minimal manual intervention, while ensuring maximum model accuracy:

356EBA0F-C36A-4589-95AD-91B939248B06@4xCreated with sketchtool.

Dataset production

Combine active learning with model integration to accelerate dataset preparation, as models pre-annotate items prior to manual labeling. Annotators then only audit pre-labeled data instead of labeling from scratch

356EBA0F-C36A-4589-95AD-91B939248B06@4xCreated with sketchtool.

Data auditing

Turn the annotation process into a model auditing task - run models on your data to receive visual representations of object recognition. Annotators then audit model output by fixing errors and identifying false negatives / positives

356EBA0F-C36A-4589-95AD-91B939248B06@4xCreated with sketchtool.

Setting thresholds

Set confidence thresholds for inferencing, sending only items with below-threshold accuracy to be annotated by humans. As models improve, manual labeling is applied only to edge-cases and random validation samples

356EBA0F-C36A-4589-95AD-91B939248B06@4xCreated with sketchtool.

Labeling in production

Close the image recognition loop even after reaching deployment in production, by sending items post-inferencing to be validated, fixed and re-applied by human annotators

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