Chaojun Shi

443 citations
27 papers · 256 · h-index 9

Impact in

Papers in

Chaojun Shi

22 papers receiving 253 citations

Peers

Chaojun Shi
Comparison fields: 5 of 44
  • Media Technology 79
  • Computer Vision and Pattern Recognition 71
  • Industrial and Manufacturing Engineering 28
  • Geophysics 34
  • Artificial Intelligence 73
Replace Lhoussaine Masmoudi with:
Lhoussaine Masmoudi Morocco
Xueyong Xu China
Xiaogang Song China
Feizhou Zhang China
Liang Han China
Wanjia Gao China
Luc Courtrai France
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Chaojun Shi relative to Lhoussaine Masmoudi Morocco Lhoussaine Masmoudi's profile →
Citations per field
00.5×6.8×
Lhoussaine Masmoudi · 1×
Citations per year

Countries citing papers authored by Chaojun Shi

Since Specialization
Citations

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

Fields of papers citing papers by Chaojun Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202043
2 201737
3 202329
4 202325
5 201921
6 202120
7 202416
8 202215
9 20249
10 20247
11 20246
12 20246
13 20234
14 20244
15 20243
16 20232
17 20242
18 20252
19 20232
20 20251

About Chaojun Shi

Chaojun Shi is a scholar working on Media Technology, Computer Vision and Pattern Recognition, Artificial Intelligence, Industrial and Manufacturing Engineering and Ecology, having authored 27 papers that have together received 256 indexed citations. Recurring topics across this work include Solar Radiation and Photovoltaics (8 papers), Advanced Image Fusion Techniques (6 papers), Advanced Neural Network Applications (6 papers), Industrial Vision Systems and Defect Detection (6 papers), Remote Sensing in Agriculture (5 papers), Remote-Sensing Image Classification (5 papers), Power Line Inspection Robots (5 papers) and Vehicle License Plate Recognition (3 papers). The work is most often cited by research in Media Technology (79 citations), Computer Vision and Pattern Recognition (71 citations), Industrial and Manufacturing Engineering (28 citations), Geophysics (34 citations) and Artificial Intelligence (73 citations). Chaojun Shi has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Bo Qiu, Yatong Zhou, Ke Zhang, Jiacun Wang, Zhenbing Zhao, Xiwang Guo, Hanming Chen, Y. J. Xiao, Yatong Zhou and Jianyong Xie. Their work appears in journals such as Atmospheric measurement techniques, IEEE Transactions on Geoscience and Remote Sensing, IEEE Transactions on Instrumentation and Measurement, IET Generation Transmission & Distribution and IEEE Geoscience and Remote Sensing Letters.

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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