Sicheng Li
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Biomedical Engineering
- Human-Computer Interaction top 5%
- Electrical and Electronic Engineering
- Topics
- Advanced Neural Network Applications (8 papers)Autonomous Vehicle Technology and Safety (3 papers)3D Shape Modeling and Analysis (3 papers)
- Journals
- Nano LettersIEEE Transactions on Circuits and Systems for Video TechnologyIEEE Transactions on Neural Systems and Rehabilitation Engineering
- Partner nations
- ChinaUnited StatesJapan
In The Last Decade
Sicheng Li
13 papers receiving 344 citations
Hit Papers
Peers
Comparison fields: 5 of 47
- Computer Vision and Pattern Recognition 267
- Artificial Intelligence 185
- Biomedical Engineering 145
- Human-Computer Interaction 57
- Electrical and Electronic Engineering 57
Countries citing papers authored by Sicheng Li
This map shows the geographic impact of Sicheng 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 Sicheng Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sicheng Li more than expected).
Fields of papers citing papers by Sicheng Li
This network shows the impact of papers produced by Sicheng 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 Sicheng Li. The network helps show where Sicheng Li may publish in the future.
Co-authorship network of co-authors of Sicheng Li
This figure shows the co-authorship network connecting the top 25 collaborators of Sicheng Li. A scholar is included among the top collaborators of Sicheng 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 Sicheng Li. Sicheng Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 3 | |
| 4 | 2 | |
| 5 | 0 | |
| 6 | 2 | |
| 7 | 1 | |
| 8 | 0 | |
| 9 | Multi-Scale Spatial Temporal Graph Convolutional Network for Skeleton-Based Action Recognitionbreakdown → | 208 |
| 10 | 0 | |
| 11 | 1 | |
| 12 | 13 | |
| 13 | Towards Efficient Hardware Acceleration of Deep Neural Networks on FPGA | 1 |
| 14 | 22 | |
| 15 | 6 | |
| 16 | 8 | |
| 17 | 80 |
About Sicheng Li
Sicheng Li is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Automotive Engineering, having authored 17 papers that have together received 348 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (8 papers), Autonomous Vehicle Technology and Safety (3 papers) and 3D Shape Modeling and Analysis (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (267 citations), Human-Computer Interaction (57 citations) and Artificial Intelligence (185 citations). Sicheng Li has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Bing Yang, Zhan Chen, Qinghan Li, Hong Liu, Hai Li, Chunpeng Wu, Boxun Li, Yu Wang, Qinru Qiu and Yiran Chen. Their work appears in journals such as Nano Letters, IEEE Transactions on Circuits and Systems for Video Technology and IEEE Transactions on Neural Systems and Rehabilitation Engineering.
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.