Shiyu Li
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 5%
- Electrical and Electronic Engineering
- Computer Networks and Communications
- Control and Systems Engineering
- Co-authors
- Yiran ChenTing ChenXi LiPing HuangXuan ZhangHai LiShinichi TakahashiMasahiro Okuda
- Topics
- Advanced Neural Network Applications (9 papers)Advanced Memory and Neural Computing (6 papers)Ferroelectric and Negative Capacitance Devices (5 papers)
- Cited by
- Computer Vision and Pattern RecognitionArtificial IntelligenceIndustrial and Manufacturing Engineering
- Partner nations
- ChinaUnited StatesJapan
In The Last Decade
Shiyu Li
43 papers receiving 396 citations
Hit Papers
Peers
Comparison fields: 5 of 86
- Artificial Intelligence 150
- Computer Vision and Pattern Recognition 144
- Electrical and Electronic Engineering 63
- Computer Networks and Communications 57
- Control and Systems Engineering 44
Countries citing papers authored by Shiyu Li
This map shows the geographic impact of Shiyu 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 Shiyu Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shiyu Li more than expected).
Fields of papers citing papers by Shiyu Li
This network shows the impact of papers produced by Shiyu 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 Shiyu Li. The network helps show where Shiyu Li may publish in the future.
Co-authorship network of co-authors of Shiyu Li
This figure shows the co-authorship network connecting the top 25 collaborators of Shiyu Li. A scholar is included among the top collaborators of Shiyu 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 Shiyu Li. Shiyu 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 | 1 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 3 | |
| 5 | 0 | |
| 6 | 7 | |
| 7 | 3 | |
| 8 | 3 | |
| 9 | 0 | |
| 10 | 2 | |
| 11 | 9 | |
| 12 | 7 | |
| 13 | 10 | |
| 14 | 8 | |
| 15 | 25 | |
| 16 | 10 | |
| 17 | PENNI: Pruned Kernel Sharing for Efficient CNN Inference | 1 |
| 18 | 10 | |
| 19 | A New BNR Process Without Sludge Discharge-the SANI Process | 1 |
| 20 | 3 |
About Shiyu Li
Shiyu Li is a scholar working on Computer Vision and Pattern Recognition, Hardware and Architecture and Paleontology, having authored 49 papers that have together received 406 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (9 papers), Advanced Memory and Neural Computing (6 papers) and Ferroelectric and Negative Capacitance Devices (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (144 citations), Artificial Intelligence (150 citations) and Industrial and Manufacturing Engineering (43 citations). Shiyu Li has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Yiran Chen, Ting Chen, Xi Li, Ping Huang, Xuan Zhang, Hai Li, Shinichi Takahashi, Masahiro Okuda, Rubén Ruíz and Dengpan Ye. Their work appears in journals such as Scientific Reports, European Journal of Operational Research and Sensors.
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.