Wei Zhong

1.9k total citations · 1 hit paper
51 papers, 1.3k citations indexed

About

Wei Zhong is a scholar working on Computer Vision and Pattern Recognition, Statistics and Probability and Artificial Intelligence. According to data from OpenAlex, Wei Zhong has authored 51 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Computer Vision and Pattern Recognition, 14 papers in Statistics and Probability and 13 papers in Artificial Intelligence. Recurrent topics in Wei Zhong's work include Statistical Methods and Inference (13 papers), Advanced Vision and Imaging (13 papers) and Bayesian Methods and Mixture Models (7 papers). Wei Zhong is often cited by papers focused on Statistical Methods and Inference (13 papers), Advanced Vision and Imaging (13 papers) and Bayesian Methods and Mixture Models (7 papers). Wei Zhong collaborates with scholars based in China, United States and Singapore. Wei Zhong's co-authors include Ming–Hsuan Yang, Huchuan Lu, Runze Li, Hengjian Cui, Li Zhu, Jingyuan Liu, Long Ye, Li Fang, Xia Wu and Xueyuan Xu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the American Statistical Association and PLoS ONE.

In The Last Decade

Wei Zhong

46 papers receiving 1.2k citations

Hit Papers

Robust object tracking via sparsity-based collaborative m... 2012 2026 2016 2021 2012 200 400 600
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Robust object tracking via sparsity-based collaborative model
    2012 741 citations Wei Zhong, Huchuan Lu et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Wei Zhong China 11 846 307 233 149 108 51 1.3k
Kumar S. Ray India 14 326 0.4× 58 0.2× 336 1.4× 61 0.4× 30 0.3× 73 778
Javier Cabrera United States 10 143 0.2× 84 0.3× 184 0.8× 22 0.1× 37 0.3× 27 730
Richard Yi Da Xu Australia 18 592 0.7× 11 0.0× 293 1.3× 107 0.7× 175 1.6× 107 1.1k
Jean-Michel Jolion France 16 1.3k 1.5× 58 0.2× 237 1.0× 85 0.6× 48 0.4× 38 1.5k
Xinge You China 21 907 1.1× 10 0.0× 355 1.5× 110 0.7× 93 0.9× 52 1.3k
Xing Sun China 19 1.2k 1.4× 14 0.0× 264 1.1× 42 0.3× 60 0.6× 52 1.4k
Di‐Rong Chen China 17 327 0.4× 94 0.3× 262 1.1× 28 0.2× 37 0.3× 79 961
Baback Moghaddam United States 15 1.0k 1.2× 31 0.1× 208 0.9× 49 0.3× 33 0.3× 28 1.3k
Keshu Zhang United States 15 336 0.4× 19 0.1× 512 2.2× 178 1.2× 133 1.2× 43 1.0k

Countries citing papers authored by Wei Zhong

Since Specialization
Citations

This map shows the geographic impact of Wei Zhong'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 Wei Zhong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wei Zhong more than expected).

Fields of papers citing papers by Wei Zhong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wei Zhong. 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 Wei Zhong. The network helps show where Wei Zhong may publish in the future.

Co-authorship network of co-authors of Wei Zhong

This figure shows the co-authorship network connecting the top 25 collaborators of Wei Zhong. A scholar is included among the top collaborators of Wei Zhong 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 Wei Zhong. Wei Zhong 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.
Gong, Ming, et al.. (2024). MISNet: multi-source information-shared EEG emotion recognition network with two-stream structure. Frontiers in Neuroscience. 18. 1293962–1293962. 3 indexed citations
2.
Wang, Xin, et al.. (2024). Probability-weighted clustered coefficient regression models in complex survey sampling. Electronic Journal of Statistics. 18(2).
3.
Zhong, Wei, et al.. (2024). Mind to Music: An EEG Signal‐Driven Real‐Time Emotional Music Generation System. International Journal of Intelligent Systems. 2024(1). 2 indexed citations
4.
Zhong, Wei, et al.. (2023). GSCNN: Gender-Sensitive EEG Emotion Recognition Using Convolutional Neural Network. 1–6. 1 indexed citations
5.
Zhong, Wei, et al.. (2023). Semi-Distance Correlation and Its Applications. Journal of the American Statistical Association. 119(548). 2919–2933. 2 indexed citations
6.
Yang, Qiang, et al.. (2023). Gender-Sensitive EEG Channel Selection for Emotion Recognition Using Enhanced Genetic Algorithm. 3253–3258. 3 indexed citations
7.
Zhong, Wei, Qian Chen, Wanjun Liu, Li Zhu, & Runze Li. (2022). Feature Screening for Interval-Valued Response with Application to Study Association between Posted Salary and Required Skills. Journal of the American Statistical Association. 118(542). 805–817. 4 indexed citations
8.
Fang, Li, et al.. (2022). Flexible Light Field Angular Superresolution via a Deep Coarse‐to‐Fine Framework. Wireless Communications and Mobile Computing. 2022(1). 1 indexed citations
9.
Zhong, Wei, et al.. (2022). Learning to generate emotional music correlated with music structure features. SHILAP Revista de lepidopterología. 4(2). 100–107. 6 indexed citations
10.
Ye, Long, et al.. (2022). Benchmarking the Robustness of Object Detection Based on Near‐Real Military Scenes. Wireless Communications and Mobile Computing. 2022(1). 2 indexed citations
11.
Zhong, Wei, et al.. (2021). Censored mean variance sure independence screening for ultrahigh dimensional survival data. Computational Statistics & Data Analysis. 159. 107206–107206. 5 indexed citations
12.
13.
Zhong, Wei, et al.. (2019). Fine-Grained Footstep Image Classification. 1. 1–6. 1 indexed citations
14.
Zhong, Wei, et al.. (2018). Forward Additive Regression for Ultrahigh Dimensional Nonparametric Additive Models. Statistica Sinica. 3 indexed citations
15.
Cui, Hengjian, et al.. (2018). Test for high-dimensional regression coefficients using refitted cross-validation variance estimation. The Annals of Statistics. 46(3). 23 indexed citations
16.
Zhu, Li, et al.. (2017). Projection correlation between two random vectors. Biometrika. 104(4). 829–843. 59 indexed citations
17.
Zhong, Wei, Li Zhu, Runze Li, & Hengjian Cui. (2015). Regularized quantile regression and robust feature screening for single index models. Statistica Sinica. 26(1). 69–95. 29 indexed citations
18.
Cui, Hengjian, Runze Li, & Wei Zhong. (2014). Model-Free Feature Screening for Ultrahigh Dimensional Discriminant Analysis. Journal of the American Statistical Association. 110(510). 630–641. 151 indexed citations
19.
Zhong, Wei, Huchuan Lu, & Ming–Hsuan Yang. (2012). Robust object tracking via sparsity-based collaborative model. 1838–1845. 741 indexed citations breakdown →
20.
Zhong, Wei. (2007). Evaluation on Volatility Forecasting Performance of GARCH-Type Models. Zhongguo guanli kexue. 1 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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