Chun‐Na Li

1.5k total citations
71 papers, 1.1k citations indexed

About

Chun‐Na Li is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Mechanics. According to data from OpenAlex, Chun‐Na Li has authored 71 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Computer Vision and Pattern Recognition, 39 papers in Artificial Intelligence and 20 papers in Computational Mechanics. Recurrent topics in Chun‐Na Li's work include Face and Expression Recognition (54 papers), Machine Learning and ELM (19 papers) and Sparse and Compressive Sensing Techniques (17 papers). Chun‐Na Li is often cited by papers focused on Face and Expression Recognition (54 papers), Machine Learning and ELM (19 papers) and Sparse and Compressive Sensing Techniques (17 papers). Chun‐Na Li collaborates with scholars based in China, Australia and United States. Chun‐Na Li's co-authors include Yuan‐Hai Shao, Nai-Yang Deng, Wei-Jie Chen, Zhen Wang, Shenglan Chen, Yanru Guo, Lan Bai, Wotao Yin, Liming Liu and Zhimin Yang and has published in prestigious journals such as European Journal of Operational Research, IEEE Access and Pattern Recognition.

In The Last Decade

Chun‐Na Li

62 papers receiving 1.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Chun‐Na Li China 19 695 561 185 183 161 71 1.1k
Wei-Jie Chen China 20 823 1.2× 790 1.4× 114 0.6× 294 1.6× 103 0.6× 57 1.3k
Reshma Rastogi India 21 706 1.0× 734 1.3× 90 0.5× 252 1.4× 86 0.5× 67 1.3k
Lingfeng Niu China 16 447 0.6× 711 1.3× 155 0.8× 71 0.4× 58 0.4× 82 1.2k
Julio López Chile 17 351 0.5× 708 1.3× 96 0.5× 108 0.6× 31 0.2× 54 1.2k
Zhimin Yang China 17 507 0.7× 387 0.7× 60 0.3× 123 0.7× 51 0.3× 59 1.0k
Pei-Yi Hao Taiwan 12 262 0.4× 404 0.7× 23 0.1× 126 0.7× 49 0.3× 30 793
S. R. Balasundaram India 16 259 0.4× 535 1.0× 117 0.6× 72 0.4× 15 0.1× 96 873
Shie-Jue Lee Taiwan 21 330 0.5× 1.0k 1.8× 31 0.2× 197 1.1× 38 0.2× 120 1.8k

Countries citing papers authored by Chun‐Na Li

Since Specialization
Citations

This map shows the geographic impact of Chun‐Na Li's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Chun‐Na Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chun‐Na Li more than expected).

Fields of papers citing papers by Chun‐Na Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chun‐Na Li. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Chun‐Na Li. The network helps show where Chun‐Na Li may publish in the future.

Co-authorship network of co-authors of Chun‐Na Li

This figure shows the co-authorship network connecting the top 25 collaborators of Chun‐Na Li. A scholar is included among the top collaborators of Chun‐Na Li based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Chun‐Na Li. Chun‐Na Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Shao, Yuan‐Hai, et al.. (2024). Large-scale robust regression with truncated loss via majorization-minimization algorithm. European Journal of Operational Research. 319(2). 494–504.
2.
Shao, Yuan‐Hai, et al.. (2024). A novel regularization method for decorrelation learning of non-parallel hyperplanes. Information Sciences. 667. 120461–120461.
3.
Li, Chun‐Na, et al.. (2024). Feature selection by Universum embedding. Pattern Recognition. 153. 110514–110514. 3 indexed citations
4.
Zhu, Tingting, et al.. (2024). Learning using granularity statistical invariants for classification. Applied Intelligence. 54(8). 6667–6681.
5.
Liu, Ju, et al.. (2023). A nonlinear kernel SVM classifier via L0/1 soft-margin loss with classification performance. Journal of Computational and Applied Mathematics. 437. 115471–115471. 5 indexed citations
6.
Li, Chun‐Na, et al.. (2023). Union nonparallel support vector machines framework with consistency. Applied Soft Computing. 136. 110129–110129. 3 indexed citations
7.
Wang, Donglin, et al.. (2023). Creating Universum for class imbalance via locality and its application in multiview subspace learning. Information Sciences. 647. 119478–119478. 3 indexed citations
8.
Li, Chun‐Na, et al.. (2023). DNTC: An unsupervised Deep Networks for Temperature Compensation in non-stationary data. Engineering Applications of Artificial Intelligence. 127. 107319–107319. 2 indexed citations
9.
Liu, Yang, et al.. (2023). A combined aerodynamic parameter identification method for missing test data. Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University. 41(2). 282–292.
10.
Shao, Yuan‐Hai, et al.. (2023). A multistage deep imputation framework for missing values large segment imputation with statistical metrics. Applied Soft Computing. 146. 110654–110654. 9 indexed citations
11.
Li, Chun‐Na, et al.. (2023). Recursive universum linear discriminant analysis. Optimization Letters. 18(6). 1405–1419.
12.
Chen, Shenglan, et al.. (2022). Financial technology as a driver of poverty alleviation in China: Evidence from an innovative regression approach. Journal of Innovation & Knowledge. 7(1). 100164–100164. 69 indexed citations
13.
Li, Chun‐Na, et al.. (2022). Capped L 1 -Norm Proximal Support Vector Machine. Mathematical Problems in Engineering. 2022. 1–18. 1 indexed citations
14.
Li, Chun‐Na, et al.. (2022). F $F$‐norm two‐dimensional linear discriminant analysis and its application on face recognition. International Journal of Intelligent Systems. 37(11). 8327–8347. 2 indexed citations
15.
Guo, Yanru, Yanqin Bai, Chun‐Na Li, Lan Bai, & Yuan‐Hai Shao. (2021). Two-dimensional Bhattacharyya bound linear discriminant analysis with its applications. Applied Intelligence. 52(8). 8793–8809. 7 indexed citations
16.
Li, Chun‐Na, Yuan‐Hai Shao, Wei-Jie Chen, Zhen Wang, & Nai-Yang Deng. (2021). Generalized two-dimensional linear discriminant analysis with regularization. Neural Networks. 142. 73–91. 17 indexed citations
17.
Shao, Yuan‐Hai, et al.. (2021). A sparse approach for high-dimensional data with heavy-tailed noise. Economic Research-Ekonomska Istraživanja. 35(1). 2764–2780. 4 indexed citations
18.
Gao, Junbin, et al.. (2020). Robust support vector regression with generic quadratic nonconvex ε-insensitive loss. Applied Mathematical Modelling. 82. 235–251. 33 indexed citations
19.
Jiang, Yuexiang, et al.. (2017). L1-Norm Least Squares Support Vector Regression via the Alternating Direction Method of Multipliers. Journal of Advanced Computational Intelligence and Intelligent Informatics. 21(6). 1017–1025. 5 indexed citations
20.
Jiang, Yuexiang, et al.. (2015). Financial Conditions Index Construction Through WeightedLp-Norm Support Vector Regression. Journal of Advanced Computational Intelligence and Intelligent Informatics. 19(3). 397–406. 8 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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2026