Liang Ye

143 total papers · 1.2k total citations
62 papers, 733 citations indexed

About

Liang Ye is a scholar working on Computer Vision and Pattern Recognition, Molecular Biology and Information Systems. According to data from OpenAlex, Liang Ye has authored 62 papers receiving a total of 733 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Computer Vision and Pattern Recognition, 9 papers in Molecular Biology and 8 papers in Information Systems. Recurrent topics in Liang Ye's work include Remote-Sensing Image Classification (6 papers), Energy, Environment, Economic Growth (4 papers) and Advanced Image Fusion Techniques (4 papers). Liang Ye is often cited by papers focused on Remote-Sensing Image Classification (6 papers), Energy, Environment, Economic Growth (4 papers) and Advanced Image Fusion Techniques (4 papers). Liang Ye collaborates with scholars based in China, United States and Finland. Liang Ye's co-authors include Zhiguo Cao, Yang Xiao, Zhujun Jiang, Matthew King, Yun Zhang, Gregory D. May, Abhijit Sanyal, Stéphane Deschamps, Haining Lin and Víctor Llaca and has published in prestigious journals such as Nature Communications, PLoS ONE and Journal of Cleaner Production.

In The Last Decade

Liang Ye

59 papers receiving 715 citations

Author Peers

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

Author						Papers	Cites
Liang Ye	148	131	114	109	97	62	733
Qing Guo	49 0.3×	89 0.7×	70 0.6×	178 1.6×	11 0.1×	46	872
Saptarsi Goswami	84 0.6×	50 0.4×	53 0.5×	350 3.2×	18 0.2×	50	857
Rong Liu	62 0.4×	49 0.4×	138 1.2×	87 0.8×	12 0.1×	65	750
Tao Zeng	106 0.7×	89 0.7×	23 0.2×	183 1.7×	94 1.0×	47	847
Muhammad Shahid Iqbal	54 0.4×	44 0.3×	98 0.9×	111 1.0×	21 0.2×	51	728
David Opeoluwa Oyewola	47 0.3×	44 0.3×	121 1.1×	194 1.8×	17 0.2×	37	843
Ye Zheng	81 0.5×	11 0.1×	102 0.9×	104 1.0×	38 0.4×	61	761
Yunyi Zhang	49 0.3×	36 0.3×	26 0.2×	247 2.3×	12 0.1×	70	856
Chiagoziem C. Ukwuoma	43 0.3×	14 0.1×	106 0.9×	361 3.3×	35 0.4×	79	852
Muhammad Aqib	20 0.1×	54 0.4×	178 1.6×	78 0.7×	14 0.1×	36	644

Countries citing papers authored by Liang Ye

Since Specialization

Citations

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

Fields of papers citing papers by Liang Ye

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Liang Ye

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