Qingsong Lv
- Artificial Intelligence top 5%
- Management Science and Operations Research top 5%
- Computer Vision and Pattern Recognition top 10%
- Information Systems top 10%
- Statistical and Nonlinear Physics top 10%
- Co-authors
- Xiaohan LanYu ZhangZhichun WangYuxiao DongJie TangQiang LiuYuxiang ChenWenzheng Feng
- Topics
- Topic Modeling (4 papers)Multimodal Machine Learning Applications (3 papers)Vibration and Dynamic Analysis (2 papers)
- Cited by
- Management Science and Operations ResearchArtificial IntelligenceComputer Vision and Pattern Recognition
- Journals
- Chemical CommunicationsIEEE Transactions on Circuits and Systems for Video TechnologyIEEE Transactions on Instrumentation and Measurement
- Partner nations
- ChinaUnited StatesIsrael
In The Last Decade
Qingsong Lv
13 papers receiving 558 citations
Hit Papers
Peers
Comparison fields: 5 of 62
- Artificial Intelligence 462
- Management Science and Operations Research 187
- Computer Vision and Pattern Recognition 118
- Information Systems 73
- Statistical and Nonlinear Physics 55
Countries citing papers authored by Qingsong Lv
This map shows the geographic impact of Qingsong Lv'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 Qingsong Lv with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qingsong Lv more than expected).
Fields of papers citing papers by Qingsong Lv
This network shows the impact of papers produced by Qingsong Lv. 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 Qingsong Lv. The network helps show where Qingsong Lv may publish in the future.
Co-authorship network of co-authors of Qingsong Lv
This figure shows the co-authorship network connecting the top 25 collaborators of Qingsong Lv. A scholar is included among the top collaborators of Qingsong Lv 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 Qingsong Lv. Qingsong Lv 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 | 2 | |
| 4 | 43 | |
| 5 | 2 | |
| 6 | 11 | |
| 7 | 9 | |
| 8 | 2 | |
| 9 | 135 | |
| 10 | Cross-lingual Knowledge Graph Alignment via Graph Convolutional Networksbreakdown → | 345 |
| 11 | 3 | |
| 12 | 3 | |
| 13 | TPL-PCRUN Statement of methods | 2 |
| 14 | 14 |
About Qingsong Lv
Qingsong Lv is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction and Artificial Intelligence, having authored 14 papers that have together received 572 indexed citations. Recurring topics across this work include Topic Modeling (4 papers), Multimodal Machine Learning Applications (3 papers) and Vibration and Dynamic Analysis (2 papers). The work is most often cited by research in Management Science and Operations Research (187 citations), Artificial Intelligence (462 citations) and Computer Vision and Pattern Recognition (118 citations). Qingsong Lv has collaborated with scholars based in China, United States and Israel. Frequent co-authors include Xiaohan Lan, Yu Zhang, Zhichun Wang, Yuxiao Dong, Jie Tang, Qiang Liu, Yuxiang Chen, Wenzheng Feng, Jianguo Jiang and Ming Ding. Their work appears in journals such as Chemical Communications, IEEE Transactions on Circuits and Systems for Video Technology and IEEE Transactions on Instrumentation and Measurement.
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.