MIAD: A Maintenance Inspection Dataset for Unsupervised Anomaly Detection
Author:
Affiliation:
1. SenseTime Research
2. JD.com, Inc.
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10350357/10350360/10350876.pdf?arnumber=10350876
Reference40 articles.
1. Beyond Dents and Scratches: Logical Constraints in Unsupervised Anomaly Detection and Localization
2. MVTec AD — A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection
3. The MVTec 3D-AD Dataset for Unsupervised 3D Anomaly Detection and Localization
4. Improving Unsupervised Defect Segmentation by Applying Structural Similarity to Autoencoders
5. Improving quality inspection of food products by computer vision––a review
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