Multiclass Defect Classification
Multiclass Defect Classification is a supervised learning task in computer vision that categorizes detected defects into multiple predefined, distinct classes based on their visual characteristics, distinguishing it from binary or single-class defect detection by enabling simultaneous identification of diverse defect types.
86
Publications
4.1K
Citations
275
Authors
151
Institutions
Publications per year
2017–2026
50
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University of Science and Technology Liaoning
Anshan, China
9 h-index
23 publications
893 citations

Northeastern University
Shenyang, China
3 h-index
7 publications
200 citations
Lakehead University
Thunder Bay, Canada
3 h-index
3 publications
99 citations
State Key Laboratory of Industrial Control Technology
Hangzhou, China
2 h-index
10 publications
370 citations

Hanyang University
Seoul, South Korea
2 h-index
4 publications
137 citations
Toronto Metropolitan University
Toronto, Canada
2 h-index
2 publications
88 citations
Southern Methodist University
Dallas, United States
2 h-index
9 publications
386 citations
Aalborg University
Aalborg, Denmark
2 h-index
5 publications
291 citations
1–8 of 151
8 publications · 697 citations
8
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5 publications · 257 citations
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3 publications · 116 citations
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2 publications · 174 citations
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2 publications · 99 citations
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