Real-time Defect Classification
Real-Time Defect Classification is a computational method in quality assurance systems that enables the immediate identification and categorization of defects during the manufacturing or operational process, distinguished by its capability to process and classify data instantaneously with minimal latency.
80
Publications
4.4K
Citations
330
Authors
131
Institutions
Publications per year
2017–2026
59
Parents
80
DeepJIT: An End-to-End Deep Learning Framework for Just-in-Time Defect Prediction
Thong Hoang, Hoa Khanh Dam, Yasutaka Kamei et al. · 2019 · 214 citations
1–5 of 80
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131
Wuhan University
Wuhan, China
3 h-index
7 publications
240 citations

Huazhong University of Science and Technology
Wuhan, China
3 h-index
17 publications
794 citations
Tsinghua University
Beijing, China
2 h-index
3 publications
100 citations
University of Patras
Pátrai, Greece
2 h-index
13 publications
572 citations

Xi'an Jiaotong University
Xi'an, China
2 h-index
5 publications
430 citations

Zhejiang University
Hangzhou, China
2 h-index
10 publications
2.4K citations

University of Wollongong
Wollongong, Australia
2 h-index
10 publications
1K citations

University of Birmingham
Birmingham, United Kingdom
2 h-index
3 publications
112 citations
1–8 of 131
3 publications · 158 citations
3
h-index
3 publications · 103 citations
3
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2 publications · 111 citations
2
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2 publications · 113 citations
2
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2 publications · 203 citations
2
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1–5