Anchor Set Optimization is a methodological framework within psychometric and educational measurement research that systematically selects and refines a subset of common items (the anchor set) to equate different test forms while minimizing measurement bias and maximizing the precision and stability of linking parameters across administrations.
8
Publications
718
Citations
34
Authors
17
Institutions
Publications per year
2017–2026
8
Parents
Publications
8
Anchor Box Optimization for Object Detection
Yuanyi Zhong, Jianfeng Wang, Jian Peng et al. · 2020 · 103 citations
A YOLO-Based Table Detection Method
Yilun Huang, Qinqin Yan, Yibo Li et al. · 2019 · 86 citations
1–5 of 8
Authors
34
- YZ
2
h-index
- LZ
2
h-index
- JP
2
h-index
- JW
2
h-index
- XW
1
h-index
1–5 of 34
Institutions
17
Xijing Hospital
Xi’an, China
1 h-index
3 publications
117 citations
Sejong University
Seoul, South Korea
1 h-index
3 publications
90 citations
Shandong University
Jinan, China
1 h-index
1 publications
39 citations
Peking University
Beijing, China
1 h-index
4 publications
344 citations
University of Science and Technology of China
Hefei, China
1 h-index
1 publications
39 citations
University of Illinois Urbana-Champaign
Urbana, United States
1 h-index
2 publications
206 citations
Hefei University of Technology
Hefei, China
1 h-index
6 publications
312 citations
National Science Centre
Krakow, Poland
1 h-index
1 publications
39 citations
1–8 of 17
Venues
- IEEE Access
1 publications · 57 citations
1
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- arXiv (Cornell University)
Repository · 1 publications · 15 citations
1
h-index
- Neural Networks
1 publications · 39 citations
1
h-index
- 2020 International Conference on Electronics, Information, and Communication (ICEIC)
Conference · 1 publications · 30 citations
1
h-index
- IEEE Transactions on Instrumentation and Measurement
1 publications · 336 citations
1
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1–5