Jinghui Qin

1.5k total citations
54 papers, 695 citations indexed

About

Jinghui Qin is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Jinghui Qin has authored 54 papers receiving a total of 695 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Artificial Intelligence, 20 papers in Computer Vision and Pattern Recognition and 11 papers in Information Systems. Recurrent topics in Jinghui Qin's work include Topic Modeling (14 papers), Multimodal Machine Learning Applications (7 papers) and Natural Language Processing Techniques (6 papers). Jinghui Qin is often cited by papers focused on Topic Modeling (14 papers), Multimodal Machine Learning Applications (7 papers) and Natural Language Processing Techniques (6 papers). Jinghui Qin collaborates with scholars based in China, United States and Hong Kong. Jinghui Qin's co-authors include Wushao Wen, Liang Lin, Yongjie Huang, Xiaodan Liang, Zhao Luo, Zheng Ye, Jianheng Tang, Jiaqi Chen, Xin Shen and Gang Wang and has published in prestigious journals such as IEEE Transactions on Image Processing, Chemical Physics Letters and Expert Systems with Applications.

In The Last Decade

Jinghui Qin

48 papers receiving 679 citations

Peers

Jinghui Qin
Comparison fields: 5 of 75
  • Artificial Intelligence 278
  • Computer Vision and Pattern Recognition 219
  • Electrical and Electronic Engineering 125
  • Information Systems 109
  • Media Technology 80
Replace K. Duraiswamy with:
K. Duraiswamy India
Zhi-Jie Wang China
La The Vinh South Korea
Daeseon Choi South Korea
Chengwei Zhang China
Patrick Marques Ciarelli Brazil
Yi Zhu China
Zhuzhu Wang China
Bo Jiang China
K. Duraiswamy India View profile →
Citations per field, relative to Jinghui Qin
Jinghui Qin · 1×
Citations per year, relative to Jinghui Qin
Jinghui Qin · 1×

Countries citing papers authored by Jinghui Qin

Since Specialization
Citations

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

Fields of papers citing papers by Jinghui Qin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jinghui Qin

This figure shows the co-authorship network connecting the top 25 collaborators of Jinghui Qin. A scholar is included among the top collaborators of Jinghui Qin 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 Jinghui Qin. Jinghui Qin 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 10
2 0
3 1
4 1
5 5
6 0
7 0
8 4
9 4
10 7
11 0
12 5
13 5
14 81
15 2
16 1
17 16
18 16
19 48
20 3

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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