Kun Shang

46 total papers · 724 total citations
20 papers, 524 citations indexed

About

Kun Shang is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Computational Mechanics. According to data from OpenAlex, Kun Shang has authored 20 papers receiving a total of 524 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Vision and Pattern Recognition, 4 papers in Signal Processing and 4 papers in Computational Mechanics. 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 United States. Kun Shang's co-authors include Ru‐Xi Ding, Xueqing Wang, Francisco Herrera, Zheng‐Hai Huang, Huaming Wu, Bingsheng Liu, Kai Yuan, Zhonglai Wang, Ning‐Cong Xiao 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 512 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Kun Shang 181 171 126 81 69 20 524
Jiarong Shi 95 0.5× 124 0.7× 211 1.7× 27 0.3× 26 0.4× 36 606
Yunzhang Zhu 74 0.4× 47 0.3× 176 1.4× 25 0.3× 28 0.4× 19 487
Kuang Zhou 88 0.5× 78 0.5× 277 2.2× 126 1.6× 30 0.4× 34 581
Stephen J. Wright 88 0.5× 50 0.3× 218 1.7× 16 0.2× 27 0.4× 16 598
Yi Yang 111 0.6× 222 1.3× 277 2.2× 27 0.3× 32 0.5× 34 535
Gavin Taylor 136 0.8× 46 0.3× 356 2.8× 39 0.5× 33 0.5× 19 595
Ryohei Fujimaki 73 0.4× 50 0.3× 309 2.5× 42 0.5× 87 1.3× 40 503
Pannagadatta K. Shivaswamy 164 0.9× 74 0.4× 372 3.0× 13 0.2× 29 0.4× 15 588
Quan Lin 58 0.3× 104 0.6× 177 1.4× 71 0.9× 18 0.3× 26 447
Cheng Zhang 69 0.4× 23 0.1× 265 2.1× 24 0.3× 31 0.4× 18 480

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

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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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