Gaihua Wang

591 total citations
42 papers, 400 citations indexed

About

Gaihua Wang is a scholar working on Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics and Media Technology. According to data from OpenAlex, Gaihua Wang has authored 42 papers receiving a total of 400 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Computer Vision and Pattern Recognition, 9 papers in Statistical and Nonlinear Physics and 9 papers in Media Technology. Recurrent topics in Gaihua Wang's work include Advanced Neural Network Applications (15 papers), Nonlinear Waves and Solitons (9 papers) and Nonlinear Photonic Systems (7 papers). Gaihua Wang is often cited by papers focused on Advanced Neural Network Applications (15 papers), Nonlinear Waves and Solitons (9 papers) and Nonlinear Photonic Systems (7 papers). Gaihua Wang collaborates with scholars based in China, Finland and Russia. Gaihua Wang's co-authors include Yang Liu, Hong Liu, Dehua Li, Jingsong He, Q.P. Liu, Wei Xiong, Yan Li, Jiguang Rao, Jing Zhang and Lihong V. Wang and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Gaihua Wang

38 papers receiving 388 citations

Peers

Gaihua Wang
Comparison fields: 5 of 89
  • Computer Vision and Pattern Recognition 182
  • Media Technology 95
  • Statistical and Nonlinear Physics 87
  • Geometry and Topology 41
  • Computational Mechanics 39
Replace Frédéric Cao with:
Frédéric Cao France
Xiang Ying China
Raghav Subbarao United States
Baojiang Zhong China
Y. Xiong China
Muhammad Kashif Iqbal Pakistan
Basarab Mateï France
B. V. Landau United Kingdom
Daniel Fontijne Netherlands
Boxi Wu China
Frédéric Cao France View profile →
Citations per field, relative to Gaihua Wang
Gaihua Wang · 1×
Citations per year, relative to Gaihua Wang
Gaihua Wang · 1×

Countries citing papers authored by Gaihua Wang

Since Specialization
Citations

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

Fields of papers citing papers by Gaihua Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gaihua Wang

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

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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