Jianqing Liang
- Molecular Biology
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Immunology
- Oncology
- Topics
- Face and Expression Recognition (7 papers)Advanced Image and Video Retrieval Techniques (5 papers)Advanced Graph Neural Networks (4 papers)
- Journals
- Journal of Biological ChemistryNature CommunicationsIEEE Transactions on Pattern Analysis and Machine Intelligence
- Partner nations
- ChinaHong KongUnited Kingdom
In The Last Decade
Jianqing Liang
36 papers receiving 615 citations
Peers
Comparison fields: 5 of 99
- Molecular Biology 160
- Computer Vision and Pattern Recognition 152
- Artificial Intelligence 119
- Immunology 101
- Oncology 81
Countries citing papers authored by Jianqing Liang
This map shows the geographic impact of Jianqing Liang'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 Jianqing Liang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jianqing Liang more than expected).
Fields of papers citing papers by Jianqing Liang
This network shows the impact of papers produced by Jianqing Liang. 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 Jianqing Liang. The network helps show where Jianqing Liang may publish in the future.
Co-authorship network of co-authors of Jianqing Liang
This figure shows the co-authorship network connecting the top 25 collaborators of Jianqing Liang. A scholar is included among the top collaborators of Jianqing Liang 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 Jianqing Liang. Jianqing Liang 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 | 15 | |
| 4 | 2 | |
| 5 | 44 | |
| 6 | 1 | |
| 7 | 25 | |
| 8 | 5 | |
| 9 | 75 | |
| 10 | 17 | |
| 11 | 19 | |
| 12 | 37 | |
| 13 | 27 | |
| 14 | 50 | |
| 15 | 37 | |
| 16 | Multiple Kernel Geometric Mean Metric Learning for Heterogeneous Data | 1 |
| 17 | 20 | |
| 18 | 19 | |
| 19 | 3 | |
| 20 | Clipping based MC-CDMA system with lower peak-to-average power ratio | 3 |
About Jianqing Liang
Jianqing Liang is a scholar working on Computer Vision and Pattern Recognition, Applied Microbiology and Biotechnology and Geology, having authored 40 papers that have together received 626 indexed citations. Recurring topics across this work include Face and Expression Recognition (7 papers), Advanced Image and Video Retrieval Techniques (5 papers) and Advanced Graph Neural Networks (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (152 citations), Immunology (101 citations) and Artificial Intelligence (119 citations). Jianqing Liang has collaborated with scholars based in China, Hong Kong and United Kingdom. Frequent co-authors include Jiye Liang, Qinghua Hu, Youhua Liu, Bing Zhao, Feilong Cao, Chuangyin Dang, Ming Li, Wangmeng Zuo, Jie Wang and Xiaoning Wang. Their work appears in journals such as Journal of Biological Chemistry, Nature Communications and IEEE Transactions on Pattern Analysis and Machine Intelligence.
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.