khornlund/severstal-steel-defect-detection
Kaggle Segmentation Challenge
This project helps steel manufacturing engineers automatically identify and classify surface defects on steel sheets using images. It takes raw images of steel surfaces as input and outputs segmented images that highlight and label different types of defects. Quality control and operations managers in steel production plants would use this to improve efficiency and maintain high product quality.
263 stars. No commits in the last 6 months.
Use this if you need to quickly and accurately detect common surface defects like 'patches', 'pitted surface', 'scrathes', and 'rolled-in scale' on steel during manufacturing.
Not ideal if you need to detect highly unusual or very subtle defects that are not well-represented in existing training data, or if you require real-time, ultra-low-latency detection on a production line without any post-processing.
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Last pushed
Oct 07, 2020
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