Chunna Tian

1.3k total citations
60 papers, 870 citations indexed

About

Chunna Tian is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Artificial Intelligence. According to data from OpenAlex, Chunna Tian has authored 60 papers receiving a total of 870 indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Computer Vision and Pattern Recognition, 15 papers in Media Technology and 8 papers in Artificial Intelligence. Recurrent topics in Chunna Tian's work include Face recognition and analysis (11 papers), Advanced Neural Network Applications (9 papers) and Face and Expression Recognition (9 papers). Chunna Tian is often cited by papers focused on Face recognition and analysis (11 papers), Advanced Neural Network Applications (9 papers) and Face and Expression Recognition (9 papers). Chunna Tian collaborates with scholars based in China, United States and Australia. Chunna Tian's co-authors include Xinbo Gao, Wei Wei, Yanning Zhang, Zhenxi Zhang, Lei Zhang, Jie Li, Heng Zhou, Zhongbo Li, Yongqiang Xie and Chengyang Li and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, IEEE Transactions on Image Processing and IEEE Access.

In The Last Decade

Chunna Tian

56 papers receiving 841 citations

Peers

Chunna Tian
Comparison fields: 5 of 82
  • Computer Vision and Pattern Recognition 622
  • Media Technology 265
  • Artificial Intelligence 97
  • Signal Processing 96
  • Computational Mechanics 90
Replace Wai-Kuen Cham with:
Wai-Kuen Cham Hong Kong
Ruizhen Zhao China
Shuangyan Yi China
Haitao Zhao China
Zhenjiang Miao China
Joseph Ronsin France
K. Etemad United States
Alberto Rosales Mexico
Atalay Barkana Türkiye
Wai-Kuen Cham Hong Kong View profile →
Citations per field, relative to Chunna Tian
Chunna Tian · 1×
Citations per year, relative to Chunna Tian
Chunna Tian · 1×

Countries citing papers authored by Chunna Tian

Since Specialization
Citations

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

Fields of papers citing papers by Chunna Tian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chunna Tian

This figure shows the co-authorship network connecting the top 25 collaborators of Chunna Tian. A scholar is included among the top collaborators of Chunna Tian 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 Chunna Tian. Chunna Tian 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 2
2 1
3 0
4 2
5 3
6 10
7 4
8 5
9 7
10 27
11 17
12 31
13 31
14 17
15 30
16 36
17 12
18 60
19 22
20 7

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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