Chengyang Li

811 total citations · 1 hit paper
19 papers, 535 citations indexed

About

Chengyang Li is a scholar working on Computer Vision and Pattern Recognition, Mechanical Engineering and Biomedical Engineering. According to data from OpenAlex, Chengyang Li has authored 19 papers receiving a total of 535 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Vision and Pattern Recognition, 6 papers in Mechanical Engineering and 4 papers in Biomedical Engineering. Recurrent topics in Chengyang Li's work include Video Surveillance and Tracking Methods (4 papers), Human Pose and Action Recognition (3 papers) and Advanced Materials and Mechanics (3 papers). Chengyang Li is often cited by papers focused on Video Surveillance and Tracking Methods (4 papers), Human Pose and Action Recognition (3 papers) and Advanced Materials and Mechanics (3 papers). Chengyang Li collaborates with scholars based in China, United States and Australia. Chengyang Li's co-authors include Ruofeng Tong, Dan Song, Min Tang, Derrick Wing Kwan Ng, Yonina C. Eldar, Chengzhong Xu, H. Vincent Poor, Liping Zhu, Jianguo He and Guoling Wan and has published in prestigious journals such as Pattern Recognition, Cement and Concrete Composites and Composite Structures.

In The Last Decade

Chengyang Li

17 papers receiving 517 citations

Hit Papers

Illumination-aware faster R-CNN for robust multispectral ... 2018 2026 2020 2023 2018 100 200 300

Peers

Chengyang Li
Comparison fields: 5 of 79
  • Computer Vision and Pattern Recognition 340
  • Media Technology 121
  • Aerospace Engineering 118
  • Artificial Intelligence 78
  • Electrical and Electronic Engineering 54
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Citations per field, relative to Chengyang Li
Chengyang Li · 1×
Citations per year, relative to Chengyang Li
Chengyang Li · 1×

Countries citing papers authored by Chengyang Li

Since Specialization
Citations

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

Fields of papers citing papers by Chengyang Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chengyang Li

This figure shows the co-authorship network connecting the top 25 collaborators of Chengyang Li. A scholar is included among the top collaborators of Chengyang Li 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 Chengyang Li. Chengyang Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
# Work Indexed citations
1 0
2 0
3 4
4 4
5 13
6 4
7 1
8 4
9 6
10 1
11 6
12 53
13 9
14 2
15 45
16 31
17
Illumination-aware faster R-CNN for robust multispectral pedestrian detection breakdown →
322
18 18
19 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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