Ye Liu

112 total papers · 1.5k total citations
74 papers, 1.1k citations indexed

About

Ye Liu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Mechanics. According to data from OpenAlex, Ye Liu has authored 74 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 59 papers in Computer Vision and Pattern Recognition, 11 papers in Artificial Intelligence and 9 papers in Computational Mechanics. Recurrent topics in Ye Liu's work include Video Surveillance and Tracking Methods (16 papers), Advanced Neural Network Applications (12 papers) and Human Pose and Action Recognition (12 papers). Ye Liu is often cited by papers focused on Video Surveillance and Tracking Methods (16 papers), Advanced Neural Network Applications (12 papers) and Human Pose and Action Recognition (12 papers). Ye Liu collaborates with scholars based in China, Macao and Singapore. Ye Liu's co-authors include Li-Hua Gong, Ting Hu, Jun Liu, Yan Qiu Chen, C. Ou-Yang, Jun Wang, Jinghui Fan, Guyue Zhang, Hao Gao and Guo‐Ping Jiang and has published in prestigious journals such as PLoS ONE, Sensors and Information Sciences.

In The Last Decade

Ye Liu

63 papers receiving 1.1k citations

Author Peers

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

Author Last Decade Papers Cites
Ye Liu 889 201 190 84 84 74 1.1k
Enrique Efrén García-Guerrero 498 0.6× 180 0.9× 133 0.7× 37 0.4× 310 3.7× 43 1.1k
Jianhua Wu 825 0.9× 234 1.2× 76 0.4× 70 0.8× 53 0.6× 72 1.3k
André Ricardo Backes 622 0.7× 216 1.1× 32 0.2× 28 0.3× 50 0.6× 95 1.1k
Wei Feng 778 0.9× 226 1.1× 180 0.9× 117 1.4× 281 3.3× 53 1.3k
Xuncai Zhang 614 0.7× 364 1.8× 300 1.6× 73 0.9× 177 2.1× 99 1.3k
Chen Xu 578 0.7× 245 1.2× 39 0.2× 18 0.2× 33 0.4× 55 1.0k
Sergio Callegari 400 0.4× 184 0.9× 324 1.7× 39 0.5× 313 3.7× 65 1.0k
Naglaa F. Soliman 582 0.7× 284 1.4× 34 0.2× 17 0.2× 30 0.4× 135 1.4k
Wen Huang 109 0.1× 125 0.6× 139 0.7× 44 0.5× 36 0.4× 72 1000
Yuanyuan Liu 430 0.5× 331 1.6× 68 0.4× 20 0.2× 43 0.5× 85 1.3k

Countries citing papers authored by Ye Liu

Since Specialization
Citations

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

Fields of papers citing papers by Ye Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ye Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Ye Liu. A scholar is included among the top collaborators of Ye Liu 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 Ye Liu. Ye Liu 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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