Peiyan Dong
- Electrical and Electronic Engineering
- Artificial Intelligence
- Computer Vision and Pattern Recognition top 10%
- Hardware and Architecture
- Signal Processing
- Topics
- CCD and CMOS Imaging Sensors (9 papers)Advanced Neural Network Applications (9 papers)Advanced Memory and Neural Computing (5 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE Transactions on Pattern Analysis and Machine IntelligenceInternational Journal of Computer Vision
- Partner nations
- United StatesMexicoChina
In The Last Decade
Peiyan Dong
23 papers receiving 210 citations
Peers
Comparison fields: 5 of 46
- Electrical and Electronic Engineering 81
- Artificial Intelligence 76
- Computer Vision and Pattern Recognition 69
- Hardware and Architecture 23
- Signal Processing 19
Countries citing papers authored by Peiyan Dong
This map shows the geographic impact of Peiyan Dong'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 Peiyan Dong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peiyan Dong more than expected).
Fields of papers citing papers by Peiyan Dong
This network shows the impact of papers produced by Peiyan Dong. 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 Peiyan Dong. The network helps show where Peiyan Dong may publish in the future.
Co-authorship network of co-authors of Peiyan Dong
This figure shows the co-authorship network connecting the top 25 collaborators of Peiyan Dong. A scholar is included among the top collaborators of Peiyan Dong 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 Peiyan Dong. Peiyan Dong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 14 | |
| 4 | 10 | |
| 5 | 6 | |
| 6 | 3 | |
| 7 | 1 | |
| 8 | 10 | |
| 9 | 2 | |
| 10 | 3 | |
| 11 | 1 | |
| 12 | 0 | |
| 13 | 1 | |
| 14 | 4 | |
| 15 | 9 | |
| 16 | 11 | |
| 17 | 2 | |
| 18 | 23 | |
| 19 | HFSP: A Hardware-friendly Soft Pruning Framework for Vision Transformers | 1 |
| 20 | 35 |
About Peiyan Dong
Peiyan Dong is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Artificial Intelligence, having authored 25 papers that have together received 214 indexed citations. Recurring topics across this work include CCD and CMOS Imaging Sensors (9 papers), Advanced Neural Network Applications (9 papers) and Advanced Memory and Neural Computing (5 papers). The work is most often cited by research in Hardware and Architecture (23 citations), Computer Vision and Pattern Recognition (69 citations) and Artificial Intelligence (76 citations). Peiyan Dong has collaborated with scholars based in United States, Mexico and China. Frequent co-authors include Yanzhi Wang, Zhengang Li, Zhenglun Kong, Mengshu Sun, Xue Lin, Sheng Lin, Xin Meng, Alec Lu, Zhenman Fang and Xue Lin. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and International Journal of Computer Vision.
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.