6x Faster Video Annotation for King's College London

Ulrik Stig Hansen
December 16, 2022
3 min read
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King's College London used Encord to achieve a 6.4x average increase in labeling efficiency for GI videos.


Using clinicians to annotate pre-cancerous polyp videos had prohibitively high costs to produce large datasets.


Deployed Encord's micro-model module to increase clinician labeling efficiency and automate 97% of produced labels.


The highest-expense clinician saw a 16x labeling efficiency improvement. Cut model development time from 1 year to 2 months.

  • 6.4X faster than manual labeling
  • 97% automated labels
  • 6X faster to AI in production

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