Fangfang Lu

584 total citations
46 papers, 354 citations indexed

About

Fangfang Lu is a scholar working on Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics and Artificial Intelligence. According to data from OpenAlex, Fangfang Lu has authored 46 papers receiving a total of 354 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Computer Vision and Pattern Recognition, 6 papers in Statistical and Nonlinear Physics and 6 papers in Artificial Intelligence. Recurrent topics in Fangfang Lu's work include Chaos control and synchronization (6 papers), Computer Graphics and Visualization Techniques (5 papers) and COVID-19 diagnosis using AI (5 papers). Fangfang Lu is often cited by papers focused on Chaos control and synchronization (6 papers), Computer Graphics and Visualization Techniques (5 papers) and COVID-19 diagnosis using AI (5 papers). Fangfang Lu collaborates with scholars based in China, Singapore and Australia. Fangfang Lu's co-authors include Ting Zhang, Jingjing Chen, Daolin Xu, Pengfei Xia, Zhihao Zhang, Lingling Guo, Yi Du, Xin Ji, Xin Wang and Hao Zhou and has published in prestigious journals such as Journal of Applied Physics, International Journal of Hydrogen Energy and Expert Systems with Applications.

In The Last Decade

Fangfang Lu

43 papers receiving 339 citations

Peers

Fangfang Lu
Comparison fields: 5 of 86
  • Computer Vision and Pattern Recognition 129
  • Ocean Engineering 69
  • Mechanics of Materials 56
  • Artificial Intelligence 50
  • Mechanical Engineering 48
Replace Zhiyu Yang with:
Zhiyu Yang China
Xiaohong Wu China
Jiangnan Zhang China
Xiaohua Zhang China
Matteo Cacciola Italy
Weimin Peng China
Ruijin Cang United States
Siyu Tang China
Zhiyu Yang China View profile →
Citations per field, relative to Fangfang Lu
Fangfang Lu · 1×
Citations per year, relative to Fangfang Lu
Fangfang Lu · 1×

Countries citing papers authored by Fangfang Lu

Since Specialization
Citations

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

Fields of papers citing papers by Fangfang Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fangfang Lu

This figure shows the co-authorship network connecting the top 25 collaborators of Fangfang Lu. A scholar is included among the top collaborators of Fangfang Lu 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 Fangfang Lu. Fangfang Lu 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 1
2 1
3 1
4 1
5 0
6 3
7 0
8 6
9 10
10 3
11 6
12 5
13 5
14 17
15 32
16 9
17 1
18 1
19 2
20 1

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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