Jun Tao

904 citations
60 papers · 586 · h-index 13

Impact in

Papers in

Jun Tao

58 papers receiving 573 citations

Peers

Jun Tao
Comparison fields: 5 of 95
  • Computer Graphics and Computer-Aided Design 109
  • Computer Vision and Pattern Recognition 295
  • Signal Processing 80
  • Computer Science Applications 31
  • Artificial Intelligence 115
Replace Hans Hagen with:
Hans Hagen Germany
Livia Marcellino Italy
Jonathan Woodring United States
Lloyd A. Treinish United States
Sizhe Wang China
Mike Sips Germany
Koji Koyamada Japan
Kevin Verbeek Netherlands
Mahsa Mirzargar United States
Chenhui Li China
Jun Tao relative to Hans Hagen Germany Hans Hagen's profile →
Citations per field
00.5×5.5×
Hans Hagen · 1×
Citations per year

Countries citing papers authored by Jun Tao

Since Specialization
Citations

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

Fields of papers citing papers by Jun Tao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 60 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201869
2 201259
3 201842
4 201931
5 201628
6 202228
7 201721
8 202218
9 201314
10 201213
11 201913
12 201813
13 201412
14 201612
15 202211
16 201311
17 201410
18 201510
19 20229
20 20229

About Jun Tao

Jun Tao is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design, Artificial Intelligence, Signal Processing and Information Systems, having authored 60 papers that have together received 586 indexed citations. Recurring topics across this work include Data Visualization and Analytics (18 papers), Computer Graphics and Visualization Techniques (16 papers), Video Analysis and Summarization (8 papers), Advanced Vision and Imaging (7 papers), Time Series Analysis and Forecasting (6 papers), Data Management and Algorithms (5 papers), Image Retrieval and Classification Techniques (5 papers) and Atmospheric chemistry and aerosols (3 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (109 citations), Computer Vision and Pattern Recognition (295 citations), Signal Processing (80 citations), Computer Science Applications (31 citations) and Artificial Intelligence (115 citations). Jun Tao has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Chaoli Wang, Ching-Kuang Shene, Jun Han, Jun Ma, Nitesh V. Chawla, Chao Huang, Hanqi Guo, Zhisheng Zhang, Jun Ma and Hao Zheng. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Computers & Graphics, Visual Informatics, Applied Sciences and Proceedings of the National Academy of Sciences.

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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