Jun Tan
Impact in
- Automotive Engineering top 5%
- Advanced Battery Technologies Research
- Transportation and Mobility Innovations
-
- Handwritten Text Recognition Techniques
Papers in
-
- Handwritten Text Recognition Techniques 20
- Image Processing and 3D Reconstruction 10
-
- AI in cancer detection 7
- Co-authors
- Lingfeng Wang (10 shared papers)Ning Bi (17 shared papers)Bin Zheng (12 shared papers)Dror Lederman (7 shared papers)Xingwei Wang (5 shared papers)Jianhuang Lai (9 shared papers)Ping Xiao (3 shared papers)Eddie López‐Honorato (3 shared papers)
- Journals
- Medical Physics (9 papers)Ore Geology Reviews (3 papers)Academic Radiology (3 papers)Physics in Medicine and Biology (3 papers)IEEE Transactions on Smart Grid (3 papers)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Jun Tan
127 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 146
- Automotive Engineering 300
- Computer Vision and Pattern Recognition 261
- Ceramics and Composites 57
- Radiology, Nuclear Medicine and Imaging 194
- Artificial Intelligence 284
Countries citing papers authored by Jun Tan
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
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.
All Works
Showing the 20 most-cited of 143 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 203 | |
| 2 | 2011 | 59 | |
| 3 | 2020 | 57 | |
| 4 | 1998 | 55 | |
| 5 | 2011 | 53 | |
| 6 | 2022 | 49 | |
| 7 | 2010 | 46 | |
| 8 | 2018 | 38 | |
| 9 | 2019 | 36 | |
| 10 | 2021 | 32 | |
| 11 | 2016 | 31 | |
| 12 | 2010 | 31 | |
| 13 | 2010 | 30 | |
| 14 | 2010 | 25 | |
| 15 | 2012 | 25 | |
| 16 | 2023 | 25 | |
| 17 | 2012 | 23 | |
| 18 | 2022 | 23 | |
| 19 | 2018 | 22 | |
| 20 | 2015 | 22 |
About Jun Tan
Jun Tan is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Automotive Engineering, Media Technology and Pulmonary and Respiratory Medicine, having authored 143 papers that have together received 1.5k indexed citations. Recurring topics across this work include Handwritten Text Recognition Techniques (20 papers), Electric Vehicles and Infrastructure (12 papers), Advanced Battery Technologies Research (11 papers), Image Processing and 3D Reconstruction (10 papers), Lung Cancer Diagnosis and Treatment (9 papers), Vehicle License Plate Recognition (8 papers), Advanced Radiotherapy Techniques (7 papers) and AI in cancer detection (7 papers). The work is most often cited by research in Automotive Engineering (300 citations), Computer Vision and Pattern Recognition (261 citations), Ceramics and Composites (57 citations), Radiology, Nuclear Medicine and Imaging (194 citations) and Artificial Intelligence (284 citations). Jun Tan has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Lingfeng Wang, Ning Bi, Bin Zheng, Dror Lederman, Xingwei Wang, Jianhuang Lai, Ping Xiao, Eddie López‐Honorato, Xiao Hui Wang and Ching Y. Suen. Their work appears in journals such as Medical Physics, Ore Geology Reviews, Academic Radiology, Physics in Medicine and Biology and IEEE Transactions on Smart Grid.
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.