Jun Yuan

1.2k citations
36 papers · 770 · h-index 15

Impact in

Papers in

Jun Yuan

32 papers receiving 752 citations

Peers

Jun Yuan
Comparison fields: 5 of 96
  • Computer Vision and Pattern Recognition 386
  • Artificial Intelligence 267
  • Signal Processing 57
  • Radiation 35
  • Materials Chemistry 179
Replace Changjian Chen with:
Changjian Chen China
Antonina Starita Italy
Anirban Chakraborty India
Li Yao China
Russell A. Kirsch United States
Peng Sun China
Andreas Wichert Portugal
R. Ananthanarayanan India
Yanzhao Wu United States
Khizar Hayat Pakistan
Jun Yuan relative to Changjian Chen China Changjian Chen's profile →
Citations per field
00.5×10×17×
Changjian Chen · 1×
Citations per year

Countries citing papers authored by Jun Yuan

Since Specialization
Citations

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

Fields of papers citing papers by Jun Yuan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020163
2 2016114
3 202185
4 202054
5 202052
6 202035
7 202233
8 201733
9 201424
10 201921
11 201921
12 201620
13 201220
14 202318
15 202115
16 200513
17 202011
18
ADSC Submission at THUMOS Challenge 2015
20158
19 20226
20 20066

About Jun Yuan

Jun Yuan is a scholar working on Artificial Intelligence, Materials Chemistry, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Radiation, having authored 36 papers that have together received 770 indexed citations. Recurring topics across this work include Luminescence Properties of Advanced Materials (11 papers), Anomaly Detection Techniques and Applications (6 papers), Radiation Detection and Scintillator Technologies (6 papers), Data Visualization and Analytics (5 papers), Nanoplatforms for cancer theranostics (4 papers), Human Pose and Action Recognition (3 papers), Perovskite Materials and Applications (3 papers) and VLSI and FPGA Design Techniques (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (386 citations), Artificial Intelligence (267 citations), Signal Processing (57 citations), Radiation (35 citations) and Materials Chemistry (179 citations). Jun Yuan has collaborated with scholars based in China, Singapore and Netherlands. Frequent co-authors include Shi‐Xia Liu, Ashraf A. Kassim, Changjian Chen, Bingbing Ni, Jiazhi Xia, Mengchen Liu, Xiaokang Yang, Weikai Yang, Langping Tu and Hong Zhang. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Laser & Photonics Review, IEEE Transactions on Circuits and Systems for Video Technology, Angewandte Chemie International Edition and Computational Visual Media.

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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