Cunhe Li

432 citations
34 papers · 314 · h-index 10

Impact in

Papers in

Cunhe Li

32 papers receiving 283 citations

Peers

Cunhe Li
Comparison fields: 5 of 52
  • Control and Systems Engineering 100
  • Artificial Intelligence 116
  • Electrical and Electronic Engineering 149
  • Computer Vision and Pattern Recognition 46
  • Mechanical Engineering 53
Replace Arıf Iqbal with:
Arıf Iqbal India
Shahid Hussain Pakistan
N.I. Santoso United States
D.G. Ece Türkiye
Shengguo Hu China
Seyed‐Alireza Ahmadi Iran
Stefan Kilyeni Romania
Masugi Inoue Japan
S. K. Choi South Korea
Aimin Zhang China
Cunhe Li relative to Arıf Iqbal India Arıf Iqbal's profile →
Citations per field
00.5×4.4×
Arıf Iqbal · 1×
Citations per year

Countries citing papers authored by Cunhe Li

Since Specialization
Citations

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

Fields of papers citing papers by Cunhe Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 24 scholars most cited alongside Cunhe 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 Cunhe Li Line = papers co-authored together Cunhe 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 201766
2 200952
3 200927
4
Improvement of Learning Algorithm for the Multi-instance Multi-label RBF Neural Networks Trained with Imbalanced Samples*
201315
5 201015
6 201814
7 202213
8 201611
9 201810
10 202110
11 20129
12 20169
13 20187
14 20207
15 20167
16 20226
17 20186
18 20254
19
Extraction of Informative Blocks from Web Pages Based on VIPS
20104
20 20073

About Cunhe Li

Cunhe Li is a scholar working on Electrical and Electronic Engineering, Control and Systems Engineering, Artificial Intelligence, Computer Vision and Pattern Recognition and Electronic, Optical and Magnetic Materials, having authored 34 papers that have together received 314 indexed citations. Recurring topics across this work include Electric Motor Design and Analysis (13 papers), Magnetic Bearings and Levitation Dynamics (7 papers), Multilevel Inverters and Converters (6 papers), Text and Document Classification Technologies (6 papers), Magnetic Properties and Applications (5 papers), Sensorless Control of Electric Motors (5 papers), Advanced Image and Video Retrieval Techniques (4 papers) and Advanced Algorithms and Applications (3 papers). The work is most often cited by research in Control and Systems Engineering (100 citations), Artificial Intelligence (116 citations), Electrical and Electronic Engineering (149 citations), Computer Vision and Pattern Recognition (46 citations) and Mechanical Engineering (53 citations). Cunhe Li has collaborated with scholars based in China, Indonesia and Australia. Frequent co-authors include Guofeng Wang, Aide Xu, Yan Li, Yunsheng Fan, Hongxia Wang, Kangwei Liu, Xing Liu, Yan Li, Cunshan Zhang and Mingwen Shao. Their work appears in journals such as Applied Intelligence, Applied Sciences, Advanced Theory and Simulations, IET Electric Power Applications and Review of Scientific Instruments.

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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