Mingzhu Shen

29 total papers · 688 total citations
7 papers, 313 citations indexed

About

Mingzhu Shen is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Mingzhu Shen has authored 7 papers receiving a total of 313 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computer Vision and Pattern Recognition, 4 papers in Artificial Intelligence and 2 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Mingzhu Shen's work include Advanced Neural Network Applications (5 papers), Domain Adaptation and Few-Shot Learning (2 papers) and Graph Theory and Algorithms (1 paper). Mingzhu Shen is often cited by papers focused on Advanced Neural Network Applications (5 papers), Domain Adaptation and Few-Shot Learning (2 papers) and Graph Theory and Algorithms (1 paper). Mingzhu Shen collaborates with scholars based in China, United States and United Kingdom. Mingzhu Shen's co-authors include Ruihao Gong, Fengwei Yu, Xianglong Liu, Haotong Qin, Ziran Wei, Jingkuan Song, Wanli Ouyang, Wenfeng Song, Ming Liu and Lixia Song and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Frontiers in Nutrition and 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

In The Last Decade

Mingzhu Shen

7 papers receiving 306 citations

Author Peers

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

Author Last Decade Papers Cites
Mingzhu Shen 205 136 50 24 22 7 313
R Meghana 115 0.6× 72 0.5× 25 0.5× 23 1.0× 37 1.7× 6 340
Валентина Кустикова 129 0.6× 61 0.4× 26 0.5× 29 1.2× 11 0.5× 7 266
Tanvir Ahmad 102 0.5× 92 0.7× 21 0.4× 34 1.4× 12 0.5× 7 332
Mayank Arya Chandra 73 0.4× 77 0.6× 13 0.3× 28 1.2× 30 1.4× 7 333
Hussam Qassim 139 0.7× 99 0.7× 18 0.4× 40 1.7× 32 1.5× 4 345
Gaofeng Ren 236 1.2× 25 0.2× 19 0.4× 46 1.9× 11 0.5× 6 340
Gongfan Fang 160 0.8× 154 1.1× 19 0.4× 14 0.6× 15 0.7× 11 309
Mohammadreza Iman 70 0.3× 101 0.7× 32 0.6× 20 0.8× 26 1.2× 5 336
Qinghao Hu 204 1.0× 125 0.9× 35 0.7× 30 1.3× 5 0.2× 14 311
G Divya 98 0.5× 67 0.5× 23 0.5× 20 0.8× 36 1.6× 6 318

Countries citing papers authored by Mingzhu Shen

Since Specialization
Citations

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

Fields of papers citing papers by Mingzhu Shen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mingzhu Shen

This figure shows the co-authorship network connecting the top 25 collaborators of Mingzhu Shen. A scholar is included among the top collaborators of Mingzhu Shen 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 Mingzhu Shen. Mingzhu Shen 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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2026