Lei Qi
- Computer Vision and Pattern Recognition top 1%
- Artificial Intelligence top 2%
- Radiology, Nuclear Medicine and Imaging top 5%
- Cognitive Neuroscience top 10%
- Biomedical Engineering
- Co-authors
- Yinghuan ShiYang GaoLihe YangLei WangWei ZhuoLitong FengWei ZhangYongsheng Yang
- Topics
- Domain Adaptation and Few-Shot Learning (29 papers)Advanced Neural Network Applications (29 papers)Video Surveillance and Tracking Methods (20 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Image Processing
- Partner nations
- ChinaAustraliaUnited States
In The Last Decade
Lei Qi
95 papers receiving 2.1k citations
Hit Papers
Peers
Comparison fields: 5 of 123
- Computer Vision and Pattern Recognition 1.1k
- Artificial Intelligence 740
- Radiology, Nuclear Medicine and Imaging 234
- Cognitive Neuroscience 229
- Biomedical Engineering 216
Countries citing papers authored by Lei Qi
This map shows the geographic impact of Lei Qi'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 Lei Qi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lei Qi more than expected).
Fields of papers citing papers by Lei Qi
This network shows the impact of papers produced by Lei Qi. 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 Lei Qi. The network helps show where Lei Qi may publish in the future.
Co-authorship network of co-authors of Lei Qi
This figure shows the co-authorship network connecting the top 25 collaborators of Lei Qi. A scholar is included among the top collaborators of Lei Qi 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 Lei Qi. Lei Qi 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 | 5 | |
| 3 | 3 | |
| 4 | 1 | |
| 5 | 5 | |
| 6 | 1 | |
| 7 | 0 | |
| 8 | 1 | |
| 9 | 0 | |
| 10 | 9 | |
| 11 | 4 | |
| 12 | 5 | |
| 13 | 17 | |
| 14 | 0 | |
| 15 | 1 | |
| 16 | 7 | |
| 17 | 21 | |
| 18 | 48 | |
| 19 | 102 | |
| 20 | Research on Weak-supervised Person Re-identification | 2 |
About Lei Qi
Lei Qi is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing, having authored 109 papers that have together received 2.1k indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (29 papers), Advanced Neural Network Applications (29 papers) and Video Surveillance and Tracking Methods (20 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.1k citations), Artificial Intelligence (740 citations) and Media Technology (187 citations). Lei Qi has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Yinghuan Shi, Yang Gao, Lihe Yang, Lei Wang, Wei Zhuo, Litong Feng, Wei Zhang, Yongsheng Yang, Xinqiang Chen and Jing Huo. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Image Processing.
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.