Siwei Fu

612 citations
24 papers · 423 · h-index 12

Impact in

Papers in

Siwei Fu

24 papers receiving 410 citations

Peers

Siwei Fu
Comparison fields: 5 of 73
  • Computer Science Applications 127
  • Computer Vision and Pattern Recognition 266
  • Human-Computer Interaction 37
  • Artificial Intelligence 120
  • Signal Processing 30
Replace Renan G. Cattelan with:
Renan G. Cattelan Brazil
Purvi Saraiya United States
Ting-Hao Huang United States
Tak Yeon Lee United States
Lars Grammel Canada
Vassilis Poulopoulos Greece
Deokgun Park United States
Nurul Fazmidar Binti Mohd Noor Malaysia
Yann Riche United States
Danna Gurari United States
Siwei Fu relative to Renan G. Cattelan Brazil Renan G. Cattelan's profile →
Citations per field
00.5×5.8×
Renan G. Cattelan · 1×
Citations per year

Countries citing papers authored by Siwei Fu

Since Specialization
Citations

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

Fields of papers citing papers by Siwei Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201664
2 202064
3 201556
4 201442
5 201826
6 201823
7 202120
8 202116
9 201816
10 201916
11 202012
12 201712
13 202110
14 201810
15 20229
16 20235
17 20244
18 20194
19 20213
20
VisImages: A Large-scale, High-quality Image Corpus in Visualization Publications.
20203

About Siwei Fu

Siwei Fu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Science Applications, Sociology and Political Science and Statistical and Nonlinear Physics, having authored 24 papers that have together received 423 indexed citations. Recurring topics across this work include Data Visualization and Analytics (14 papers), Video Analysis and Summarization (7 papers), Online Learning and Analytics (4 papers), Advanced Text Analysis Techniques (3 papers), Image and Video Quality Assessment (3 papers), Complex Network Analysis Techniques (3 papers), Image Retrieval and Classification Techniques (2 papers) and Multimedia Communication and Technology (2 papers). The work is most often cited by research in Computer Science Applications (127 citations), Computer Vision and Pattern Recognition (266 citations), Human-Computer Interaction (37 citations), Artificial Intelligence (120 citations) and Signal Processing (30 citations). Siwei Fu has collaborated with scholars based in Hong Kong, China and United States. Frequent co-authors include Huamin Qu, Conglei Shi, Qing Chen, Weiwei Cui, Jian Zhao, Yingcai Wu, Yifan Wang, Zhutian Chen, Kun Zhou and Haiyi Zhu. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Computer Graphics Forum, IEEE Computer Graphics and Applications, ACM Transactions on Interactive Intelligent Systems and Journal of Image and Graphics.

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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