Min Dong

76 total papers · 468 total citations
39 papers, 302 citations indexed

About

Min Dong is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Min Dong has authored 39 papers receiving a total of 302 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Computer Vision and Pattern Recognition, 11 papers in Artificial Intelligence and 5 papers in Computer Networks and Communications. Recurrent topics in Min Dong's work include Context-Aware Activity Recognition Systems (6 papers), Human Pose and Action Recognition (6 papers) and Rough Sets and Fuzzy Logic (5 papers). Min Dong is often cited by papers focused on Context-Aware Activity Recognition Systems (6 papers), Human Pose and Action Recognition (6 papers) and Rough Sets and Fuzzy Logic (5 papers). Min Dong collaborates with scholars based in China, United States and France. Min Dong's co-authors include Yide Ma, Sheng Bi, Jiuwen Zhang, Xiangpeng Li, Bin Wu, Jiangcheng Chen, Xiao Zeng, Jingyun Xu, Yi Cai and Yunda Liu and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Sensors.

In The Last Decade

Min Dong

37 papers receiving 289 citations

Author Peers

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

Author Last Decade Papers Cites
Min Dong 132 87 59 35 34 39 302
Venkatraman Atti 111 0.8× 69 0.8× 112 1.9× 67 1.9× 43 1.3× 30 330
Adis Alihodžić 145 1.1× 161 1.9× 51 0.9× 38 1.1× 33 1.0× 25 352
Fangyuan Lei 90 0.7× 97 1.1× 37 0.6× 20 0.6× 31 0.9× 38 258
M. R. Kaimal 99 0.8× 67 0.8× 39 0.7× 13 0.4× 23 0.7× 50 348
Xian Wei 173 1.3× 133 1.5× 48 0.8× 30 0.9× 17 0.5× 17 349
Chien‐Chang Hsu 84 0.6× 85 1.0× 27 0.5× 29 0.8× 35 1.0× 27 317
Zhongqin Bi 115 0.9× 99 1.1× 112 1.9× 63 1.8× 32 0.9× 34 346
S. Arumugam 136 1.0× 83 1.0× 35 0.6× 22 0.6× 29 0.9× 50 292
Tarek M. Hamdani 152 1.2× 155 1.8× 32 0.5× 16 0.5× 19 0.6× 55 321
Rui Gao 73 0.6× 91 1.0× 31 0.5× 75 2.1× 54 1.6× 38 348

Countries citing papers authored by Min Dong

Since Specialization
Citations

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

Fields of papers citing papers by Min Dong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Min Dong

This figure shows the co-authorship network connecting the top 25 collaborators of Min Dong. A scholar is included among the top collaborators of Min Dong 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 Min Dong. Min Dong 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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