Cunbo Li

35 papers receiving 899 citations

Cunbo Li's Hit Papers

EEG Based Emotion Recognition by Combining Functional Connectivity Network and Local Activations 2019 · 310 citations
3100+2+4Years since publication100200300

Peers

Cunbo Li
Comparison fields: 5 of 107
  • Cognitive Neuroscience 651
  • Experimental and Cognitive Psychology 280
  • Human-Computer Interaction 63
  • Signal Processing 61
  • Cellular and Molecular Neuroscience 89
Replace Yingjie Li with:
Yingjie Li China
S. Salinari Italy
Yajing Si China
Xuyang Zhu China
Maie Bachmann Estonia
Pitshaporn Leelaarporn Germany
Yunyuan Gao China
Setha Pan-ngum Thailand
Kaare B. Mikkelsen Denmark
Cunbo Li relative to Yingjie Li China Yingjie Li's profile →
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Citations per year

Countries citing papers authored by Cunbo Li

Since Specialization
Citations

This map shows the geographic impact of Cunbo 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 Cunbo Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cunbo Li more than expected).

Fields of papers citing papers by Cunbo Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Cunbo 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 Cunbo Li. The network helps show where Cunbo Li may publish in the future.

Co-authors

The 25 scholars most cited alongside Cunbo 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 Cunbo Li Line = papers co-authored together Cunbo Li links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1
EEG Based Emotion Recognition by Combining Functional Connectivity Network and Local Activations
Hit paper breakdown →
2019310
2 201888
3 202371
4 201954
5 202050
6 202440
7 202036
8 201529
9 201120
10 202318
11 202217
12 202215
13 202313
14 201413
15 202212
16 202411
17 202110
18 202310
19 202310
20 20219

About Cunbo Li

Cunbo Li is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology, Molecular Biology, Cellular and Molecular Neuroscience and Signal Processing, having authored 37 papers that have together received 903 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (24 papers), Functional Brain Connectivity Studies (14 papers), Neural dynamics and brain function (10 papers), Emotion and Mood Recognition (7 papers), Blind Source Separation Techniques (3 papers), Neuroscience and Neural Engineering (3 papers), Advanced Memory and Neural Computing (2 papers) and Face and Expression Recognition (2 papers). The work is most often cited by research in Cognitive Neuroscience (651 citations), Experimental and Cognitive Psychology (280 citations), Human-Computer Interaction (63 citations), Signal Processing (61 citations) and Cellular and Molecular Neuroscience (89 citations). Cunbo Li has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Peng Xu, Peiyang Li, Fali Li, Xuyang Zhu, Yajing Si, Yangsong Zhang, Dezhong Yao, Xiaoye Huang, Dezhong Yao and Ying Zeng. Their work appears in journals such as IEEE Transactions on Neural Networks and Learning Systems, Biomedical Signal Processing and Control, IEEE Transactions on Neural Systems and Rehabilitation Engineering, Biochemical and Biophysical Research Communications and IEEE Transactions on Systems Man and Cybernetics Systems.

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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