Dianmin Sun

483 citations
18 papers · 300 · h-index 10

Impact in

Papers in

Dianmin Sun

18 papers receiving 294 citations

Peers

Dianmin Sun
Comparison fields: 5 of 80
  • Computer Vision and Pattern Recognition 89
  • Human-Computer Interaction 18
  • Cancer Research 42
  • Media Technology 20
  • Control and Systems Engineering 43
Replace Seyyed Mohammad Razavi with:
Seyyed Mohammad Razavi Iran
Xiwen Zhang China
Deyin Liu China
Yingjie Zhou China
Katsumi Yamashita Japan
Сонглин Ду China
Xiao Jin China
Jongchan Park South Korea
Jiatao Song China
Huang Cheng-bing China
Dianmin Sun relative to Seyyed Mohammad Razavi Iran Seyyed Mohammad Razavi's profile →
Citations per field
00.5×
Seyyed Mohammad Razavi · 1×
Citations per year

Countries citing papers authored by Dianmin Sun

Since Specialization
Citations

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

Fields of papers citing papers by Dianmin Sun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

18 of 18 papers shown
#Work
1 202171
2 201850
3 202034
4 202021
5 202020
6 202018
7 202016
8 202113
9 202010
10 202010
11 20209
12 20209
13 20219
14 20214
15 20213
16 20201
17 20221
18 20211

About Dianmin Sun

Dianmin Sun is a scholar working on Computer Vision and Pattern Recognition, Biomedical Engineering, Artificial Intelligence, Control and Systems Engineering and Computer Networks and Communications, having authored 18 papers that have together received 300 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (3 papers), Image Enhancement Techniques (2 papers), Human Pose and Action Recognition (2 papers), Advanced Image Processing Techniques (2 papers), Soft Robotics and Applications (2 papers), Advanced Vision and Imaging (2 papers), IoT and Edge/Fog Computing (2 papers) and Medical Imaging and Analysis (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (89 citations), Human-Computer Interaction (18 citations), Cancer Research (42 citations), Media Technology (20 citations) and Control and Systems Engineering (43 citations). Dianmin Sun has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Zhongcai Pei, Weihai Chen, Xingming Wu, Baochang Zhang, Shuwei Shao, Wentao Zhu, Shi Wang, Zhi Liu, Aiqin Liu and Bufu Tang. Their work appears in journals such as Neural Computing and Applications, Future Generation Computer Systems, Pattern Recognition Letters, Computerized Medical Imaging and Graphics and Medical Image Analysis.

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.

Explore authors with similar magnitude of impact