Unsupervised Defect Detection
Unsupervised Defect Detection is a defect detection paradigm that belongs to the class of unsupervised learning methods, distinguished by its ability to identify anomalies or defects in data without requiring labeled examples of defective instances.
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6.9K
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326
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140
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2017–2026
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MVTec AD — A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection
Paul Bergmann, Michael Fauser, David Sattlegger et al. · 2019 · 1.8K citations
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Huazhong University of Science and Technology
Wuhan, China
5 h-index
14 publications
1.3K citations
Nanyang Technological University
Singapore, Singapore
4 h-index
12 publications
370 citations

Xi'an Polytechnic University
Xi'an, China
4 h-index
10 publications
282 citations

Zhejiang University
Hangzhou, China
3 h-index
4 publications
75 citations

Beijing Institute of Technology
Beijing, China
3 h-index
3 publications
102 citations
Nanjing University
Nanjing, China
3 h-index
10 publications
641 citations
State Key Laboratory of Industrial Control Technology
Hangzhou, China
3 h-index
11 publications
387 citations
Hangzhou Normal University
Hangzhou, China
3 h-index
3 publications
102 citations
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7 publications · 594 citations
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6 publications · 256 citations
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