Weakly Supervised Defect Detection
Weakly Supervised Defect Detection is a defect detection paradigm that belongs to the class of machine learning approaches utilizing incomplete, inexact, or imprecise supervision, distinguished by its reliance on limited or coarse-grained labels—such as image-level annotations instead of pixel-level annotations—to train models for identifying defects in industrial or material inspection tasks.
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2.5K
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198
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66
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2017–2026
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Steel Surface Defect Recognition: A Survey
Xin Wen, Jvran Shan, Yu He et al. · Coatings · 2022 · 172 citations · Full text
Improving defect prediction with deep forest
Tianchi Zhou, Xiaobing Sun, Xin Xia et al. · Information and Software Technology · 2019 · 130 citations
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Northeastern University
Shenyang, China
6 h-index
24 publications
960 citations

Northwestern Polytechnical University
Xi'an, China
2 h-index
3 publications
168 citations

Zhejiang University
Hangzhou, China
2 h-index
9 publications
349 citations

Southeast University
Nanjing, China
2 h-index
7 publications
282 citations

Yangzhou University
Yangzhou, China
2 h-index
4 publications
472 citations

Huazhong University of Science and Technology
Wuhan, China
2 h-index
8 publications
244 citations

South China University of Technology
Guangzhou, China
2 h-index
5 publications
186 citations

Harbin Institute of Technology
Harbin, China
2 h-index
7 publications
140 citations
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3 publications · 67 citations
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2 publications · 60 citations
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CMIG · 2 publications · 168 citations
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2 publications · 126 citations
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2 publications · 106 citations
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