Jun Shi

2.1k citations
107 papers · 1.2k · h-index 17

Impact in

Papers in

Jun Shi

97 papers receiving 1.2k citations

Peers

Jun Shi
Comparison fields: 5 of 129
  • Computer Vision and Pattern Recognition 519
  • Media Technology 218
  • Artificial Intelligence 413
  • Industrial and Manufacturing Engineering 113
  • Radiology, Nuclear Medicine and Imaging 175
Replace Qiang Guo with:
Qiang Guo China
Yi Zhu China
Muhammad Khusairi Osman Malaysia
Sankhadeep Chatterjee India
Haibin Lin China
Qing Liu China
Yang Zhang China
Krishna Gopal Dhal India
Jonas Mueller United States
Sheng Huang China
Jun Shi relative to Qiang Guo China Qiang Guo's profile →
Citations per field
00.5×1.5×2.2×
Qiang Guo · 1×
Citations per year

Countries citing papers authored by Jun Shi

Since Specialization
Citations

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

Fields of papers citing papers by Jun Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jun Shi, 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 Shi Line = papers co-authored together Jun Shi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 107 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013255
2 202099
3 201878
4 201978
5 202139
6 201539
7 202139
8 202335
9 202331
10 202029
11 202326
12 200024
13 201322
14 202022
15 201817
16 202317
17 202116
18 202116
19 201816
20 202016

About Jun Shi

Jun Shi is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Media Technology, Radiology, Nuclear Medicine and Imaging and Atmospheric Science, having authored 107 papers that have together received 1.2k indexed citations. Recurring topics across this work include AI in cancer detection (29 papers), Advanced Image and Video Retrieval Techniques (13 papers), Image Retrieval and Classification Techniques (13 papers), Digital Imaging for Blood Diseases (10 papers), Radiomics and Machine Learning in Medical Imaging (9 papers), Face and Expression Recognition (8 papers), Cervical Cancer and HPV Research (6 papers) and Image Enhancement Techniques (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (519 citations), Media Technology (218 citations), Artificial Intelligence (413 citations), Industrial and Manufacturing Engineering (113 citations) and Radiology, Nuclear Medicine and Imaging (175 citations). Jun Shi has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Zhiguo Jiang, Fengying Xie, Yushan Zheng, Hao Feng, Long Chen, Ping Yang, Haopeng Zhang, Ruoyu Wang, Chenghai Xue and Danpei Zhao. Their work appears in journals such as Computer Methods and Programs in Biomedicine, IEEE Transactions on Medical Imaging, Medical Image Analysis, IEEE Journal of Biomedical and Health Informatics and Journal of Applied Biomedicine.

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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