Shan Li
- Computer Vision and Pattern Recognition top 0.5%
- Experimental and Cognitive Psychology top 0.5%
- Artificial Intelligence top 5%
- Signal Processing top 2%
- Cognitive Neuroscience top 5%
- Topics
- Face and Expression Recognition (10 papers)Emotion and Mood Recognition (8 papers)Face recognition and analysis (5 papers)
- Cited by
- Experimental and Cognitive PsychologyComputer Vision and Pattern RecognitionHuman-Computer Interaction
- Journals
- Proceedings of the National Academy of SciencesThe Journal of Clinical Endocrinology & MetabolismThe Plant Journal
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Shan Li
65 papers receiving 3.3k citations
Hit Papers
Peers
Comparison fields: 5 of 158
- Computer Vision and Pattern Recognition 2.0k
- Experimental and Cognitive Psychology 1.8k
- Artificial Intelligence 444
- Signal Processing 361
- Cognitive Neuroscience 359
Countries citing papers authored by Shan Li
This map shows the geographic impact of Shan Li'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 Shan Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shan Li more than expected).
Fields of papers citing papers by Shan Li
This network shows the impact of papers produced by Shan Li. 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 Shan Li. The network helps show where Shan Li may publish in the future.
Co-authorship network of co-authors of Shan Li
This figure shows the co-authorship network connecting the top 25 collaborators of Shan Li. A scholar is included among the top collaborators of Shan Li 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 Shan Li. Shan Li 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 | 0 | |
| 5 | 2 | |
| 6 | 8 | |
| 7 | 4 | |
| 8 | 1 | |
| 9 | 3 | |
| 10 | 10 | |
| 11 | 15 | |
| 12 | 18 | |
| 13 | 34 | |
| 14 | 8 | |
| 15 | 3 | |
| 16 | Reliable Crowdsourcing and Deep Locality-Preserving Learning for Unconstrained Facial Expression Recognitionbreakdown → | 447 |
| 17 | 2 | |
| 18 | Effects of capsaicin on the cholesterol lithogenesis in the gallbladder of C57BL/6 mice | 2 |
| 19 | 8 | |
| 20 | 96 |
About Shan Li
Shan Li is a scholar working on Computer Vision and Pattern Recognition, Biological Psychiatry and Experimental and Cognitive Psychology, having authored 69 papers that have together received 3.4k indexed citations. Recurring topics across this work include Face and Expression Recognition (10 papers), Emotion and Mood Recognition (8 papers) and Face recognition and analysis (5 papers). The work is most often cited by research in Experimental and Cognitive Psychology (1.8k citations), Computer Vision and Pattern Recognition (2.0k citations) and Human-Computer Interaction (217 citations). Shan Li has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Weihong Deng, Junping Du, Zhenqi Xu, Ailin Luo, Chun Yang, Bin Zhu, Gaofeng Zhan, Niannian Huang, Ling Yang and Ning Yang. Their work appears in journals such as Proceedings of the National Academy of Sciences, The Journal of Clinical Endocrinology & Metabolism and The Plant Journal.
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.