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Amazon· Bedrock / NovaEnhancing industrial safety AI with synthetic data on Amazon SageMaker AI
Synthetic data pipeline achieves 160% improvement in person detection for industrial safety AI
Amazon's guide shows how to use a synthetic data augmentation pipeline on Amazon SageMaker AI and Amazon Rekognition to generate photo-realistic training images with automated labels for industrial safety AI, achieving up to 160 percent improvement in person detection mAP50 without manual annotation or hazardous photography.
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In this post, we show how to use a synthetic data augmentation pipeline built on Amazon SageMaker AI and Amazon Rekognition to generate photo-realistic training images with automated labels. Our experiments showed up to 160 percent improvement in person detection mAP50 (mean Average Precision at an Intersection over Union threshold of 0.5) without manual annotation or hazardous photography sessions.
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