Qingyun Shi
- Computer Vision and Pattern Recognition top 2%
- Signal Processing top 2%
- Plant Science
- Computer Networks and Communications top 10%
- Artificial Intelligence
- Topics
- Image and Signal Denoising Methods (7 papers)Hydrogen Storage and Materials (7 papers)Advanced Data Compression Techniques (6 papers)
- Cited by
- Signal ProcessingComputer Vision and Pattern RecognitionGeography, Planning and Development
- Journals
- Proceedings of the National Academy of SciencesIEEE Transactions on Pattern Analysis and Machine IntelligenceApplied Catalysis B: Environmental
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Qingyun Shi
33 papers receiving 850 citations
Peers
Comparison fields: 5 of 80
- Computer Vision and Pattern Recognition 573
- Signal Processing 320
- Plant Science 106
- Computer Networks and Communications 101
- Artificial Intelligence 88
Countries citing papers authored by Qingyun Shi
This map shows the geographic impact of Qingyun Shi'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 Qingyun Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qingyun Shi more than expected).
Fields of papers citing papers by Qingyun Shi
This network shows the impact of papers produced by Qingyun Shi. 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 Qingyun Shi. The network helps show where Qingyun Shi may publish in the future.
Co-authorship network of co-authors of Qingyun Shi
This figure shows the co-authorship network connecting the top 25 collaborators of Qingyun Shi. A scholar is included among the top collaborators of Qingyun Shi 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 Qingyun Shi. Qingyun Shi 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 | 5 | |
| 3 | 7 | |
| 4 | 13 | |
| 5 | 7 | |
| 6 | 23 | |
| 7 | 13 | |
| 8 | 1 | |
| 9 | 10 | |
| 10 | 26 | |
| 11 | 70 | |
| 12 | 1 | |
| 13 | 17 | |
| 14 | 0 | |
| 15 | 22 | |
| 16 | 1 | |
| 17 | 120 | |
| 18 | 2 | |
| 19 | Quantitative Shape Recovery of an Object from A Single View. | 0 |
| 20 | 412 |
About Qingyun Shi
Qingyun Shi is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Media Technology, having authored 35 papers that have together received 905 indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (7 papers), Hydrogen Storage and Materials (7 papers) and Advanced Data Compression Techniques (6 papers). The work is most often cited by research in Signal Processing (320 citations), Computer Vision and Pattern Recognition (573 citations) and Geography, Planning and Development (45 citations). Qingyun Shi has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Shi-Kuo Chang, Pengwei Hao, Hao Zhang, Tong Lin, Ming Chen, Jinlong Lin, Zhouchen Lin, Dijun Chen, Jinwei Zhang and Yijun Meng. Their work appears in journals such as Proceedings of the National Academy of Sciences, IEEE Transactions on Pattern Analysis and Machine Intelligence and Applied Catalysis B: Environmental.
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.