Qingyao Wu
- Radiology, Nuclear Medicine and Imaging top 10%
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 5%
- Electrical and Electronic Engineering
- Pulmonary and Respiratory Medicine
- Topics
- Domain Adaptation and Few-Shot Learning (4 papers)Energy Load and Power Forecasting (3 papers)Retinal Imaging and Analysis (3 papers)
- Cited by
- Computer Vision and Pattern RecognitionRadiology, Nuclear Medicine and ImagingHealth Informatics
- Journals
- SHILAP Revista de lepidopterologíaIEEE Transactions on Power SystemsExpert Systems with Applications
- Partner nations
- ChinaHong KongUnited Kingdom
In The Last Decade
Qingyao Wu
36 papers receiving 581 citations
Peers
Comparison fields: 5 of 88
- Radiology, Nuclear Medicine and Imaging 186
- Artificial Intelligence 176
- Computer Vision and Pattern Recognition 164
- Electrical and Electronic Engineering 99
- Pulmonary and Respiratory Medicine 64
Countries citing papers authored by Qingyao Wu
This map shows the geographic impact of Qingyao Wu'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 Qingyao Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qingyao Wu more than expected).
Fields of papers citing papers by Qingyao Wu
This network shows the impact of papers produced by Qingyao Wu. 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 Qingyao Wu. The network helps show where Qingyao Wu may publish in the future.
Co-authorship network of co-authors of Qingyao Wu
This figure shows the co-authorship network connecting the top 25 collaborators of Qingyao Wu. A scholar is included among the top collaborators of Qingyao Wu 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 Qingyao Wu. Qingyao Wu 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 | 4 | |
| 4 | 0 | |
| 5 | 8 | |
| 6 | 3 | |
| 7 | 4 | |
| 8 | 6 | |
| 9 | 5 | |
| 10 | 9 | |
| 11 | 1 | |
| 12 | 2 | |
| 13 | 33 | |
| 14 | 18 | |
| 15 | 26 | |
| 16 | 17 | |
| 17 | 45 | |
| 18 | 42 | |
| 19 | 3 | |
| 20 | 33 |
About Qingyao Wu
Qingyao Wu is a scholar working on Computer Vision and Pattern Recognition, Energy Engineering and Power Technology and Industrial and Manufacturing Engineering, having authored 38 papers that have together received 604 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (4 papers), Energy Load and Power Forecasting (3 papers) and Retinal Imaging and Analysis (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (164 citations), Radiology, Nuclear Medicine and Imaging (186 citations) and Health Informatics (10 citations). Qingyao Wu has collaborated with scholars based in China, Hong Kong and United Kingdom. Frequent co-authors include Pengshuai Yin, Xiaoxin Zhou, Junpeng Zhan, Chuangxin Guo, Hanrui Wu, Yuguang Yan, Huaqing Min, Bin Li, Yifan Zhang and Junzhou Huang. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Power Systems and Expert Systems with Applications.
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.