Shan Li

5.3k citations
69 papers · 3.4k indexed · 3 hit papers · h-index 19

Shan Li

65 papers receiving 3.3k citations

Hit Papers

Deep Facial Expression Recognition: A Survey9132017202620202023250500750

Peers

Shan Li
Comparison fields: 5 of 158
  • Experimental and Cognitive Psychology 1.8k
  • Computer Vision and Pattern Recognition 2.0k
  • Human-Computer Interaction 217
  • Biological Psychiatry 87
  • Signal Processing 361
Replace Wen‐Jing Yan with:
Wen‐Jing Yan China
Ira L. Cohen United States
Guangyuan Liu China
Abhinav Dhall Australia
Xiaowei Zhang China
Fu Li China
Jiahui Pan China
Christian Müller Germany
Ian Fasel United States
Muhammad Hussain Saudi Arabia
Shan Li relative to Wen‐Jing Yan China Wen‐Jing Yan's profile →
Citations per field
00.5×5.8×
Wen‐Jing Yan · 1×
Citations per year

Countries citing papers authored by Shan Li

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

The 25 scholars most cited alongside Shan Li, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Shan Li Line = papers co-authored together Shan Li links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20251
3 20242
4 20240
5 20232
6 20238
7 20234
8 20231
9 20223
10 202210
11 202115
12 202118
13 202034
14 20208
15 20193
16
Reliable Crowdsourcing and Deep Locality-Preserving Learning for Unconstrained Facial Expression Recognitionbreakdown →
2018447
17 20182
18
Effects of capsaicin on the cholesterol lithogenesis in the gallbladder of C57BL/6 mice
20172
19 20168
20 200996

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), Face recognition and analysis (5 papers), DNA Repair Mechanisms (3 papers), EEG and Brain-Computer Interfaces (3 papers), Advanced Vision and Imaging (3 papers), Advanced Image Processing Techniques (3 papers) and RNA Research and Splicing (3 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.

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