Wenfa Li

29 total papers · 552 total citations
23 papers, 377 citations indexed

About

Wenfa Li is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Wenfa Li has authored 23 papers receiving a total of 377 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 8 papers in Computer Vision and Pattern Recognition and 5 papers in Signal Processing. Recurrent topics in Wenfa Li's work include Security and Verification in Computing (4 papers), Advanced Neural Network Applications (4 papers) and Advanced Malware Detection Techniques (4 papers). Wenfa Li is often cited by papers focused on Security and Verification in Computing (4 papers), Advanced Neural Network Applications (4 papers) and Advanced Malware Detection Techniques (4 papers). Wenfa Li collaborates with scholars based in China, United States and Russia. Wenfa Li's co-authors include Hongzhe Liu, Wei Xie, Peng Yang, Weiwei Cai, Liping Zhang, Lina Yu, Xin Ning, Dong Peng, Gongming Wang and Jie Wang and has published in prestigious journals such as PLoS ONE, IEEE Access and Information Fusion.

In The Last Decade

Wenfa Li

23 papers receiving 370 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Wenfa Li 97 76 45 33 32 23 377
Yunsheng Song 53 0.5× 105 1.4× 25 0.6× 30 0.9× 19 0.6× 19 384
Yousef Alhwaiti 97 1.0× 139 1.8× 32 0.7× 16 0.5× 37 1.2× 22 377
Kislay Raj 106 1.1× 53 0.7× 15 0.3× 22 0.7× 39 1.2× 11 351
Xiaofeng Yue 94 1.0× 84 1.1× 27 0.6× 38 1.2× 10 0.3× 22 422
Yang Shen 159 1.6× 51 0.7× 67 1.5× 12 0.4× 14 0.4× 44 415
Penghui Sun 73 0.8× 59 0.8× 20 0.4× 27 0.8× 13 0.4× 17 352
Syam Machinathu Parambil Gangadharan 66 0.7× 71 0.9× 15 0.3× 19 0.6× 35 1.1× 15 360
Hamed Taheri Gorji 56 0.6× 83 1.1× 19 0.4× 32 1.0× 23 0.7× 29 403
Chiranjibi Shah 92 0.9× 58 0.8× 56 1.2× 8 0.2× 15 0.5× 26 436
Manas Ranjan Prusty 57 0.6× 140 1.8× 60 1.3× 92 2.8× 23 0.7× 32 442

Countries citing papers authored by Wenfa Li

Since Specialization
Citations

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

Fields of papers citing papers by Wenfa Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wenfa Li

This figure shows the co-authorship network connecting the top 25 collaborators of Wenfa Li. A scholar is included among the top collaborators of Wenfa Li 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 Wenfa Li. Wenfa Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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