Enhancing industrial safety AI with synthetic data on Amazon SageMaker AI
Amazon Web Services Dimitri Voytan
Industrial safety AI pipelines using Amazon SageMaker AI and Amazon Rekognition added photo-realistic, automatically labeled synthetic images by inserting people into real equipment scenes to train person-detection models. Person detection mAP50 improved by up to 160 percent in their experiments, without manual annotation or hazardous photography sessions. The training approach changes by shifting from collecting and labeling rare high-risk images to generating labeled synthetic edge-case images via diffusion-based editing and Rekognition pseudo-labels.
Why it matters
Learn how to build a synthetic data augmentation pipeline on Amazon SageMaker AI and Amazon Rekognition that generates photo-realistic, auto-labeled training images for industrial safety AI. This approach improved person detection by up to 160% without manual annotation or hazardous data collection near heavy machinery.
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