Baobin Li

703 citations
34 papers · 409 · h-index 10

Impact in

Papers in

Baobin Li

32 papers receiving 401 citations

Peers

Baobin Li
Comparison fields: 5 of 71
  • Computer Vision and Pattern Recognition 215
  • Experimental and Cognitive Psychology 76
  • Human-Computer Interaction 23
  • Applied Psychology 17
  • Statistical and Nonlinear Physics 36
Replace Athanasia Zlatintsi with:
Athanasia Zlatintsi Greece
Değer Ayata Türkiye
Siyang Song United Kingdom
Xinzhou Xu China
Miriam Cha United States
Barry-John Theobald United Kingdom
Vedhas Pandit Germany
Jen‐Chun Lin Taiwan
Baobin Li relative to Athanasia Zlatintsi Greece Athanasia Zlatintsi's profile →
Citations per field
00.5×
Athanasia Zlatintsi · 1×
Citations per year

Countries citing papers authored by Baobin Li

Since Specialization
Citations

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

Fields of papers citing papers by Baobin Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202090
2 201951
3 201645
4 201643
5 202135
6 202017
7 201215
8 202212
9 201212
10 20129
11 20228
12 20227
13 20126
14 20096
15 20166
16 20195
17 20105
18 20085
19 20215
20 20244

About Baobin Li

Baobin Li is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Experimental and Cognitive Psychology, Social Psychology and Cognitive Neuroscience, having authored 34 papers that have together received 409 indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (7 papers), Emotion and Mood Recognition (5 papers), Mental Health via Writing (4 papers), Domain Adaptation and Few-Shot Learning (4 papers), Mental Health Research Topics (4 papers), Advanced Data Compression Techniques (4 papers), Advanced Numerical Analysis Techniques (4 papers) and Brain Tumor Detection and Classification (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (215 citations), Experimental and Cognitive Psychology (76 citations), Human-Computer Interaction (23 citations), Applied Psychology (17 citations) and Statistical and Nonlinear Physics (36 citations). Baobin Li has collaborated with scholars based in China, United States and Macao. Frequent co-authors include Tingshao Zhu, Nan Zhao, Jingying Wang, Yuanyuan Xiang, Zhan Zhang, Lizhong Peng, Shun Li, Tiejian Luo, Yameng Wang and Ben He. Their work appears in journals such as Mathematical Methods in the Applied Sciences, Mathematics and Computers in Simulation, Computer Aided Geometric Design, PeerJ and Frontiers in Public Health.

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.

Explore authors with similar magnitude of impact