Variance Shift Detection
Variance Shift Detection is a statistical process control method that identifies significant deviations in the variability of a process from its established baseline, distinguishing it from other process monitoring techniques by its specific focus on changes in variance rather than shifts in mean or other distributional parameters.
60
Publications
4.4K
Citations
131
Authors
70
Institutions
Publications per year
2017–2026
10
Parents
60
Understanding the Disharmony Between Dropout and Batch Normalization by Variance Shift
Xiang Li, Shuo Chen, Xiaolin Hu et al. · 2019 · 309 citations
Region Normalization for Image Inpainting
Tao Yu, Zongyu Guo, Xin Jin et al. · 2020 · 167 citations · Full text
1–5 of 60
131
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King Fahd University of Petroleum and Minerals, Saudi Arabia
3 publications · 73 citations
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3
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1–5 of 131
70
Nanyang Technological University
Singapore, Singapore
6 h-index
13 publications
623 citations
Quaid-i-Azam University
Islamabad, Pakistan
4 h-index
7 publications
139 citations

Universiti Sains Malaysia
George Town, Malaysia
3 h-index
4 publications
216 citations
Yuan Ze University
Taoyuan District, Taiwan
3 h-index
4 publications
152 citations
National University of Singapore
Singapore, Singapore
2 h-index
3 publications
116 citations
Shahed University
Tehran, Iran
2 h-index
7 publications
150 citations
University of Iowa
Iowa City, United States
2 h-index
3 publications
169 citations

University of Minnesota
Minneapolis, United States
2 h-index
3 publications
347 citations
1–8 of 70
8 publications · 216 citations
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8 publications · 392 citations
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7 publications · 169 citations
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4 publications · 608 citations
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3 publications · 59 citations
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