Jun Han

1.2k citations
76 papers · 774 indexed · h-index 15

Impact in

Papers in

Jun Han

70 papers receiving 739 citations

Peers

Jun Han
Comparison fields: 5 of 108
  • Computer Graphics and Computer-Aided Design 175
  • Computer Vision and Pattern Recognition 390
  • Signal Processing 76
  • Computational Mechanics 106
  • Computer Science Applications 27
Replace Johannes Kehrer with:
Johannes Kehrer Norway
Mario Lučić United States
Partha Pratim Das India
Feng Sun China
Faisal Z. Qureshi Canada
Andreas Fabri France
Mahsa Baktashmotlagh Australia
Shuyang Gu China
João L. D. Comba Brazil
Junpeng Wang United States
Jun Han relative to Johannes Kehrer Norway Johannes Kehrer's profile →
Citations per field
00.5×8.7×
Johannes Kehrer · 1×
Citations per year

Countries citing papers authored by Jun Han

Since Specialization
Citations

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

Fields of papers citing papers by Jun Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 76 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201869
2 201955
3 202042
4 202239
5 202039
6 201037
7 201936
8 202135
9 202233
10 201932
11 202032
12 200228
13 202123
14 202322
15 202218
16 201914
17 201913
18 201412
19 202211
20 201111

About Jun Han

Jun Han is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition, Computer Science Applications, Signal Processing and Information Systems, having authored 76 papers that have together received 774 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (11 papers), Advanced Image Processing Techniques (11 papers), Generative Adversarial Networks and Image Synthesis (9 papers), Fault Detection and Control Systems (7 papers), Higher Education and Teaching Methods (7 papers), Image and Signal Denoising Methods (7 papers), Flow Measurement and Analysis (6 papers) and Data Visualization and Analytics (5 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (175 citations), Computer Vision and Pattern Recognition (390 citations), Signal Processing (76 citations), Computational Mechanics (106 citations) and Computer Science Applications (27 citations). Jun Han has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Chaoli Wang, Danny Z. Chen, Jun Tao, Hao Zheng, Xuefei Chen, Jing Liu, W.H. Ku, J.R. Zeidler, Jing Liu and Li Guo. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Scientific Reports, Journal of Vision, Computers & Graphics and Frontiers in Pharmacology.

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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