matlab-deep-learning/pillQC
A pill quality control dataset and associated anomaly detection example
This project helps quality control inspectors in pill manufacturing identify defective pills by providing a dataset of normal and flawed pill images. It includes examples of dirt contamination and chip defects. The associated deep learning example shows how to train a system that takes an image of a pill and determines if it meets quality standards, making it useful for automated visual inspection.
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Use this if you need to set up or improve an automated visual inspection system for quality control in pill manufacturing.
Not ideal if your quality control needs extend beyond visual inspection of pills, or if you are not working with image-based defect detection.
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MATLAB
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May 19, 2022
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