Xiaochuan Fan

914 total citations
13 papers, 443 citations indexed

About

Xiaochuan Fan is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Biomedical Engineering. According to data from OpenAlex, Xiaochuan Fan has authored 13 papers receiving a total of 443 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Computer Vision and Pattern Recognition, 5 papers in Artificial Intelligence and 3 papers in Biomedical Engineering. Recurrent topics in Xiaochuan Fan's work include Video Surveillance and Tracking Methods (5 papers), Human Pose and Action Recognition (5 papers) and Image Retrieval and Classification Techniques (3 papers). Xiaochuan Fan is often cited by papers focused on Video Surveillance and Tracking Methods (5 papers), Human Pose and Action Recognition (5 papers) and Image Retrieval and Classification Techniques (3 papers). Xiaochuan Fan collaborates with scholars based in United States, China and United Kingdom. Xiaochuan Fan's co-authors include Song Wang, Kang Zheng, Hao Guo, Hongkai Yu, Yuewei Lin, Youjie Zhou, Chunyang Jin, Jin Chen, Xiaoqiang Wang and Feng Li and has published in prestigious journals such as PLoS Genetics, International Journal of Computer Vision and Pattern Recognition Letters.

In The Last Decade

Xiaochuan Fan

13 papers receiving 438 citations

Peers

Xiaochuan Fan
Comparison fields: 5 of 75
  • Computer Vision and Pattern Recognition 332
  • Artificial Intelligence 169
  • Human-Computer Interaction 46
  • Biomedical Engineering 46
  • Radiology, Nuclear Medicine and Imaging 42
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Carolina Reta Mexico
Jiatao Song China
Jiawen Yang China
Xianhui Liu China
Sudhir Sawarkar India
Dianmin Sun China
Mohammed Aloraini Saudi Arabia
Noelia Vállez Spain
Zhiwei Cao China
Dimitris Kastaniotis Greece
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Citations per field, relative to Xiaochuan Fan
Xiaochuan Fan · 1×
Citations per year, relative to Xiaochuan Fan
Xiaochuan Fan · 1×

Countries citing papers authored by Xiaochuan Fan

Since Specialization
Citations

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

Fields of papers citing papers by Xiaochuan Fan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaochuan Fan

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaochuan Fan. A scholar is included among the top collaborators of Xiaochuan Fan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Xiaochuan Fan. Xiaochuan Fan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

13 of 13 papers shown
# Work Indexed citations
1 4
2 14
3 9
4 159
5 32
6 23
7 17
8 37
9 21
10 5
11 11
12 99
13 12

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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