matlab-deep-learning/pillQC

A pill quality control dataset and associated anomaly detection example

36
/ 100
Emerging

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.

No commits in the last 6 months.

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.

pharmaceutical-manufacturing quality-control visual-inspection defect-detection manufacturing-automation
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 15 / 25

How are scores calculated?

Stars

11

Forks

4

Language

MATLAB

License

Last pushed

May 19, 2022

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/matlab-deep-learning/pillQC"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.