Jian‐Xun Mi

87 total papers · 1.1k total citations
56 papers, 760 citations indexed

About

Jian‐Xun Mi is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Computational Mechanics. According to data from OpenAlex, Jian‐Xun Mi has authored 56 papers receiving a total of 760 indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Computer Vision and Pattern Recognition, 16 papers in Signal Processing and 15 papers in Computational Mechanics. Recurrent topics in Jian‐Xun Mi's work include Face and Expression Recognition (28 papers), Sparse and Compressive Sensing Techniques (15 papers) and Face recognition and analysis (14 papers). Jian‐Xun Mi is often cited by papers focused on Face and Expression Recognition (28 papers), Sparse and Compressive Sensing Techniques (15 papers) and Face recognition and analysis (14 papers). Jian‐Xun Mi collaborates with scholars based in China, Hong Kong and Switzerland. Jian‐Xun Mi's co-authors include Lifang Zhou, Yong Xu, Jin‐Xing Liu, Zhihui Lai, Weisheng Li, David Zhang, Zizhu Fan, Qi Zhu, De-Shuang Huang and Bing Wang and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Image Processing and Expert Systems with Applications.

In The Last Decade

Jian‐Xun Mi

53 papers receiving 730 citations

Author Peers

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

Author Last Decade Papers Cites
Jian‐Xun Mi 389 146 132 121 108 56 760
Wei Dai 343 0.9× 198 1.4× 100 0.8× 42 0.3× 42 0.4× 91 816
Mohammad Hossein Sedaaghi 336 0.9× 120 0.8× 186 1.4× 28 0.2× 44 0.4× 64 771
Jielin Jiang 286 0.7× 40 0.3× 178 1.3× 64 0.5× 73 0.7× 51 836
Syed Fawad Hussain 220 0.6× 121 0.8× 379 2.9× 51 0.4× 31 0.3× 51 899
Jie Wang 405 1.0× 134 0.9× 297 2.3× 61 0.5× 34 0.3× 51 815
Pavan Chakraborty 338 0.9× 48 0.3× 90 0.7× 100 0.8× 17 0.2× 65 852
Julian Eggert 326 0.8× 228 1.6× 166 1.3× 23 0.2× 82 0.8× 74 858
Fengxi Song 377 1.0× 162 1.1× 212 1.6× 29 0.2× 41 0.4× 23 780
Shujian Yu 317 0.8× 142 1.0× 339 2.6× 22 0.2× 103 1.0× 65 858
Zhonghua Liu 545 1.4× 81 0.6× 243 1.8× 26 0.2× 147 1.4× 66 809

Countries citing papers authored by Jian‐Xun Mi

Since Specialization
Citations

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

Fields of papers citing papers by Jian‐Xun Mi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jian‐Xun Mi. 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 Jian‐Xun Mi. The network helps show where Jian‐Xun Mi may publish in the future.

Co-authorship network of co-authors of Jian‐Xun Mi

This figure shows the co-authorship network connecting the top 25 collaborators of Jian‐Xun Mi. A scholar is included among the top collaborators of Jian‐Xun Mi 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 Jian‐Xun Mi. Jian‐Xun Mi 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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