Jiang Zhong

420 total citations
34 papers, 198 citations indexed

About

Jiang Zhong is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Jiang Zhong has authored 34 papers receiving a total of 198 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Artificial Intelligence, 9 papers in Computer Vision and Pattern Recognition and 7 papers in Computer Networks and Communications. Recurrent topics in Jiang Zhong's work include Topic Modeling (6 papers), Advanced Neural Network Applications (6 papers) and Domain Adaptation and Few-Shot Learning (6 papers). Jiang Zhong is often cited by papers focused on Topic Modeling (6 papers), Advanced Neural Network Applications (6 papers) and Domain Adaptation and Few-Shot Learning (6 papers). Jiang Zhong collaborates with scholars based in China, Australia and Japan. Jiang Zhong's co-authors include Luosheng Wen, Xue Li, Qi Li, Qing Li, Weinan Wang, Lili Li, Wei-Li Guo, Rongzhen Li, Zhenhua Wang and Yong Feng and has published in prestigious journals such as PLoS ONE, Expert Systems with Applications and IEEE Access.

In The Last Decade

Jiang Zhong

31 papers receiving 193 citations

Peers

Jiang Zhong
Comparison fields: 5 of 59
  • Artificial Intelligence 95
  • Computer Networks and Communications 45
  • Computer Vision and Pattern Recognition 43
  • Statistical and Nonlinear Physics 26
  • Information Systems 15
Replace Xiaofeng Yu with:
Xiaofeng Yu Hong Kong
Jingyang Yuan China
Yiran Zhao China
Pavel Kordík Czechia
Piet Spiessens Belgium
Rawaa Dawoud Al-Dabbagh Iraq
Sanjay Kumar Sonbhadra India
Suhap Şahın Türkiye
Matthieu Weber Finland
Yiyang Gu China
Xiaofeng Yu Hong Kong View profile →
Citations per field, relative to Jiang Zhong
Jiang Zhong · 1×
Citations per year, relative to Jiang Zhong
Jiang Zhong · 1×

Countries citing papers authored by Jiang Zhong

Since Specialization
Citations

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

Fields of papers citing papers by Jiang Zhong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jiang Zhong

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

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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