Sheng Li

89 papers receiving 813 citations

Peers

Sheng Li
Comparison fields: 5 of 99
  • Computer Vision and Pattern Recognition 220
  • Acoustics and Ultrasonics 8
  • Signal Processing 90
  • Computational Mechanics 145
  • Artificial Intelligence 196
Replace Rajesh Mehra with:
Rajesh Mehra India
Stamatios Georgoulis Switzerland
Wen-Chung Kao Taiwan
Vikas Singh India
Hao Shen Germany
Shuxue Ding Japan
Basheera M. Mahmmod Iraq
Alfredo Gardel Spain
Hanqiu Sun Hong Kong
Ram Narayan Yadav India
Sheng Li relative to Rajesh Mehra India Rajesh Mehra's profile →
Citations per field
00.5×
Rajesh Mehra · 1×
Citations per year

Countries citing papers authored by Sheng Li

Since Specialization
Citations

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

Fields of papers citing papers by Sheng Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 104 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019111
2 201551
3 202147
4 201037
5 202132
6 202329
7 202128
8 201628
9 201627
10 202024
11 202222
12 200621
13 202020
14 201918
15 201917
16 201716
17 202214
18 202014
19 202113
20 202413

About Sheng Li

Sheng Li is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Biomedical Engineering, Mechanical Engineering and Computational Mechanics, having authored 104 papers that have together received 838 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (17 papers), Hydraulic and Pneumatic Systems (17 papers), Blind Source Separation Techniques (10 papers), Advanced Clustering Algorithms Research (9 papers), AI in cancer detection (8 papers), Image Retrieval and Classification Techniques (8 papers), Microwave Imaging and Scattering Analysis (7 papers) and Gastrointestinal Bleeding Diagnosis and Treatment (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (220 citations), Acoustics and Ultrasonics (8 citations), Signal Processing (90 citations), Computational Mechanics (145 citations) and Artificial Intelligence (196 citations). Sheng Li has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Xiongxiong He, Huang Bai, Jiajia Chen, Jian Ruan, Jinhui Zhu, Liping Chang, Thomas F. George, Yu Huang, Zhihui Zhu and Yitian Zhao. Their work appears in journals such as International Journal of Computer Assisted Radiology and Surgery, Neurocomputing, Flow Measurement and Instrumentation, Signal Processing and IEEE Transactions on Knowledge and Data Engineering.

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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