Kun Shang

731 total citations
22 papers, 527 citations indexed

About

Kun Shang is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Signal Processing. According to data from OpenAlex, Kun Shang has authored 22 papers receiving a total of 527 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Vision and Pattern Recognition, 5 papers in Computational Mechanics and 4 papers in Signal Processing. Recurrent topics in Kun Shang's work include Face and Expression Recognition (6 papers), Face recognition and analysis (5 papers) and Sparse and Compressive Sensing Techniques (4 papers). Kun Shang is often cited by papers focused on Face and Expression Recognition (6 papers), Face recognition and analysis (5 papers) and Sparse and Compressive Sensing Techniques (4 papers). Kun Shang collaborates with scholars based in China, Spain and Australia. Kun Shang's co-authors include Ru‐Xi Ding, Francisco Herrera, Xueqing Wang, Zheng‐Hai Huang, Huaming Wu, Zhonglai Wang, Ning‐Cong Xiao, Bingsheng Liu, Kai Yuan and Yufan Li and has published in prestigious journals such as Information Sciences, IEEE Transactions on Fuzzy Systems and Neurocomputing.

In The Last Decade

Kun Shang

18 papers receiving 515 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kun Shang China 12 182 171 126 81 69 22 527
Syama Sundar Rangapuram Germany 11 74 0.4× 259 1.5× 245 1.9× 63 0.8× 242 3.5× 15 746
Arnaud Martin France 15 120 0.7× 185 1.1× 474 3.8× 63 0.8× 145 2.1× 51 881
Dirk Ormoneit United States 13 157 0.9× 115 0.7× 319 2.5× 37 0.5× 50 0.7× 17 714
Ryohei Fujimaki Japan 12 73 0.4× 50 0.3× 310 2.5× 42 0.5× 87 1.3× 40 505
Xin Tong United States 13 54 0.3× 69 0.4× 207 1.6× 9 0.1× 27 0.4× 46 576
Guoqiu Wen China 13 221 1.2× 105 0.6× 306 2.4× 31 0.4× 26 0.4× 40 550
Suhrid Balakrishnan United States 11 84 0.5× 46 0.3× 229 1.8× 20 0.2× 199 2.9× 18 551
Stephan Zheng United States 7 136 0.7× 35 0.2× 300 2.4× 18 0.2× 71 1.0× 14 560

Countries citing papers authored by Kun Shang

Since Specialization
Citations

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

Fields of papers citing papers by Kun Shang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kun Shang

This figure shows the co-authorship network connecting the top 25 collaborators of Kun Shang. A scholar is included among the top collaborators of Kun Shang 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 Kun Shang. Kun Shang 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.
2.
Shang, Kun, Chia‐Hsuan Chang, & Christopher C. Yang. (2025). Collaboration among Multiple Large Language Models for Medical Question Answering. 388–396.
3.
4.
Wang, Ce, Kun Shang, Haimiao Zhang, et al.. (2023). Active CT Reconstruction with a Learned Sampling Policy. 7226–7235. 4 indexed citations
5.
Wang, Dong, Kun Shang, Huaming Wu, & Ce Wang. (2022). Decoupled R-CNN: Sensitivity-Specific Detector for Higher Accurate Localization. IEEE Transactions on Circuits and Systems for Video Technology. 32(9). 6324–6336. 25 indexed citations
6.
Shang, Kun, et al.. (2021). A generic, cluster-centred lossless compression framework for joint auroral data. Journal of Visual Communication and Image Representation. 78. 103185–103185. 1 indexed citations
7.
Ding, Ru‐Xi, Xueqing Wang, Kun Shang, & Francisco Herrera. (2019). Social network analysis-based conflict relationship investigation and conflict degree-based consensus reaching process for large scale decision making using sparse representation. Information Fusion. 50. 251–272. 141 indexed citations
8.
Yuan, Kai, Ning‐Cong Xiao, Zhonglai Wang, & Kun Shang. (2019). System reliability analysis by combining structure function and active learning kriging model. Reliability Engineering & System Safety. 195. 106734–106734. 69 indexed citations
9.
Shang, Kun, Yufan Li, & Zheng‐Hai Huang. (2019). Iterative p-shrinkage thresholding algorithm for low Tucker rank tensor recovery. Information Sciences. 482. 374–391. 19 indexed citations
10.
Chen, Zhangling, Ce Wang, Huaming Wu, Kun Shang, & Jun Wang. (2019). DMGAN: Discriminative Metric-based Generative Adversarial Networks. Knowledge-Based Systems. 192. 105370–105370. 20 indexed citations
11.
Shang, Kun, et al.. (2019). Deep compact discriminative representation for unconstrained face recognition. Signal Processing Image Communication. 75. 118–127. 8 indexed citations
12.
Li, Yufan, Kun Shang, & Zheng‐Hai Huang. (2019). A singular value p-shrinkage thresholding algorithm for low rank matrix recovery. Computational Optimization and Applications. 73(2). 453–476. 8 indexed citations
13.
Wang, Ce, Zhangling Chen, Kun Shang, & Huaming Wu. (2019). Label-removed generative adversarial networks incorporating with K-Means. Neurocomputing. 361. 126–136. 19 indexed citations
14.
Ding, Ru‐Xi, Xueqing Wang, Kun Shang, Bingsheng Liu, & Francisco Herrera. (2018). Sparse Representation-Based Intuitionistic Fuzzy Clustering Approach to Find the Group Intra-Relations and Group Leaders for Large-Scale Decision Making. IEEE Transactions on Fuzzy Systems. 27(3). 559–573. 85 indexed citations
15.
Zhang, Yanhong, et al.. (2018). Patch strategy for deep face recognition. IET Image Processing. 12(5). 819–825. 28 indexed citations
16.
Shang, Kun, et al.. (2018). Learning deep discriminative face features by customized weighted constraint. Neurocomputing. 332. 71–79. 11 indexed citations
17.
Li, Yufan, Kun Shang, & Zheng‐Hai Huang. (2017). Low Tucker rank tensor recovery via ADMM based on exact and inexact iteratively reweighted algorithms. Journal of Computational and Applied Mathematics. 331. 64–81. 20 indexed citations
18.
Shang, Kun, et al.. (2017). A single gallery-based face recognition using extended joint sparse representation. Applied Mathematics and Computation. 320. 99–115. 12 indexed citations
19.
Huang, Zheng‐Hai, et al.. (2016). A Customized Sparse Representation Model With Mixed Norm for Undersampled Face Recognition. IEEE Transactions on Information Forensics and Security. 11(10). 2203–2214. 22 indexed citations
20.
Cui, Wei, Wei Wu, Xin Wang, et al.. (2010). Development of the personalized criteria for microscopic review following four different series of hematology analyzer in a Chinese large scale hospital.. PubMed. 123(22). 3231–7. 11 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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