Prioritization of the data that needed to be annotated first, without wasting time and resources on labeling unnecessary data.
Quick visualization of data to find bad quality data to remove from annotation pipeline and bulk delete based on filter.
Find a similar image and see the level of similarity, based on which selection can be made.
Analyzing and indicating the system that generates the report on the scenarios on which model accuracy gets reduced and will suggest the kind of image it should annotate in the next batch. Find a similar image and see the level of similarity, based on which selection can be made.
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