Lei Fan

1.5k total citations
69 papers, 851 citations indexed

About

Lei Fan is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Biomedical Engineering. According to data from OpenAlex, Lei Fan has authored 69 papers receiving a total of 851 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Computer Vision and Pattern Recognition, 15 papers in Artificial Intelligence and 12 papers in Biomedical Engineering. Recurrent topics in Lei Fan's work include Advanced Neural Network Applications (7 papers), Remote-Sensing Image Classification (6 papers) and Elasticity and Material Modeling (6 papers). Lei Fan is often cited by papers focused on Advanced Neural Network Applications (7 papers), Remote-Sensing Image Classification (6 papers) and Elasticity and Material Modeling (6 papers). Lei Fan collaborates with scholars based in China, Australia and United States. Lei Fan's co-authors include Hai Li, Qingzhao Li, Xuezhen Chen, Wei Wang, Huifang Kong, Juqun Xi, Wu-Jun Li, Yang Song, Ge He and Zhilong Xu and has published in prestigious journals such as Journal of Applied Physics, Advanced Functional Materials and Carbon.

In The Last Decade

Lei Fan

62 papers receiving 829 citations

Peers

Lei Fan
Comparison fields: 5 of 134
  • Biomedical Engineering 143
  • Artificial Intelligence 132
  • Management Science and Operations Research 107
  • Materials Chemistry 106
  • Computer Vision and Pattern Recognition 103
Replace Cong Wu with:
Cong Wu China
Yingqian Zhang Netherlands
Shenghan Zhou China
Yanying Li China
Hao Peng China
Yuting Lü China
Yun Chen China
Mohd Amiruddin Abd Rahman Malaysia
Subir Chowdhury Canada
Jiquan Wang China
Cong Wu China View profile →
Citations per field, relative to Lei Fan
Lei Fan · 1×
Citations per year, relative to Lei Fan
Lei Fan · 1×

Countries citing papers authored by Lei Fan

Since Specialization
Citations

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

Fields of papers citing papers by Lei Fan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lei Fan

This figure shows the co-authorship network connecting the top 25 collaborators of Lei Fan. A scholar is included among the top collaborators of Lei Fan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Lei Fan. Lei Fan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 5
2 1
3 2
4 2
5 3
6 17
7 1
8 0
9 0
10 37
11 18
12 3
13 3
14 36
15 6
16 2
17
Employee Ridesharing: Reinforcement Learning and Choice Modeling.
1
18 25
19 2
20
Based on improved BP neural network model generating power predicting for PV system
5

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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