Jun Tan

1.9k citations
123 papers · 1.2k · h-index 19

Impact in

Papers in

Jun Tan

108 papers receiving 1.2k citations

Peers

Jun Tan
Comparison fields: 5 of 142
  • Automotive Engineering 279
  • Computer Vision and Pattern Recognition 217
  • Ceramics and Composites 55
  • Radiology, Nuclear Medicine and Imaging 206
  • Artificial Intelligence 260
Replace Zhanlin Ji with:
Zhanlin Ji China
Ruixiang Zhang China
Xu Yuan United States
Zhe Zhu China
Nagwan Abdel Samee Saudi Arabia
Lei He China
Jie Meng China
Tsubasa Hirakawa Japan
Mominul Ahsan United Kingdom
Jun Tan relative to Zhanlin Ji China Zhanlin Ji's profile →
Citations per field
00.5×4.4×
Zhanlin Ji · 1×
Citations per year

Countries citing papers authored by Jun Tan

Since Specialization
Citations

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

Fields of papers citing papers by Jun Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jun Tan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jun Tan Line = papers co-authored together Jun Tan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 123 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015197
2 201154
3 201150
4 202050
5 201044
6 199843
7 202241
8 201932
9 201831
10 201028
11 201628
12 201028
13 201522
14 201222
15 201020
16 202219
17 201219
18 201319
19 201819
20 202118

About Jun Tan

Jun Tan is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Electrical and Electronic Engineering, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine, having authored 123 papers that have together received 1.2k indexed citations. Recurring topics across this work include Handwritten Text Recognition Techniques (13 papers), Electric Vehicles and Infrastructure (11 papers), Medical Imaging Techniques and Applications (11 papers), Advanced Battery Technologies Research (10 papers), Lung Cancer Diagnosis and Treatment (10 papers), Image Processing and 3D Reconstruction (7 papers), AI in cancer detection (7 papers) and Radiomics and Machine Learning in Medical Imaging (7 papers). The work is most often cited by research in Automotive Engineering (279 citations), Computer Vision and Pattern Recognition (217 citations), Ceramics and Composites (55 citations), Radiology, Nuclear Medicine and Imaging (206 citations) and Artificial Intelligence (260 citations). Jun Tan has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Lingfeng Wang, Bin Zheng, Dror Lederman, Ning Bi, Xingwei Wang, Ping Xiao, Eddie López‐Honorato, Jianhuang Lai, Xiao Hui Wang and P.J. Meadows. Their work appears in journals such as Medical Physics, Academic Radiology, Physics in Medicine and Biology, IEEE Transactions on Smart Grid and Ore Geology Reviews.

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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