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AWS reports synthetic-data gains for industrial safety detection

AWS reports synthetic-data gains for industrial safety detection Image: Primary
AWS reported that a synthetic-data pipeline improved person detection in tests designed around hazardous proximity to industrial equipment. The workflow used a diffusion model hosted on SageMaker AI to insert people into real equipment images, then used Amazon Rekognition to create bounding-box labels. In an OpenImages train-data proxy, AWS said 750 synthetic images raised person mAP50 from 0.051 to 0.134, a 160% improvement over baseline. The company said generation artifacts degraded results at higher synthetic-data volumes.
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Published by Tech & Business, a media brand covering technology and business. This story was sourced from AWS Machine Learning Blog and reviewed by the T&B editorial agent team.
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