Qing Tian

1.1k total citations
97 papers, 767 citations indexed

About

Qing Tian is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Biomedical Engineering. According to data from OpenAlex, Qing Tian has authored 97 papers receiving a total of 767 indexed citations (citations by other indexed papers that have themselves been cited), including 65 papers in Computer Vision and Pattern Recognition, 45 papers in Artificial Intelligence and 8 papers in Biomedical Engineering. Recurrent topics in Qing Tian's work include Domain Adaptation and Few-Shot Learning (34 papers), Video Surveillance and Tracking Methods (24 papers) and Multimodal Machine Learning Applications (20 papers). Qing Tian is often cited by papers focused on Domain Adaptation and Few-Shot Learning (34 papers), Video Surveillance and Tracking Methods (24 papers) and Multimodal Machine Learning Applications (20 papers). Qing Tian collaborates with scholars based in China, United Kingdom and United States. Qing Tian's co-authors include Songcan Chen, Yun Wei, Sing H. Lee, Jinde Cao, Jianhua Guo, Wei Huang, Zu-Han Gu, Hujun Yin, Meng Cao and Yi Chu and has published in prestigious journals such as Applied Energy, IEEE Transactions on Image Processing and Sensors.

In The Last Decade

Qing Tian

82 papers receiving 743 citations

Peers

Qing Tian
Comparison fields: 5 of 97
  • Computer Vision and Pattern Recognition 464
  • Artificial Intelligence 298
  • Media Technology 94
  • Electrical and Electronic Engineering 55
  • Control and Systems Engineering 51
Replace Renjie Song with:
Renjie Song China
Gang Zhang China
Wouter Van Gansbeke Belgium
Simon Vandenhende Switzerland
Miao Ma China
Yigang Cen China
Frederick Tung Canada
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Citations per field, relative to Qing Tian
Qing Tian · 1×
Citations per year, relative to Qing Tian
Qing Tian · 1×

Countries citing papers authored by Qing Tian

Since Specialization
Citations

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

Fields of papers citing papers by Qing Tian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qing Tian

This figure shows the co-authorship network connecting the top 25 collaborators of Qing Tian. A scholar is included among the top collaborators of Qing 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 Qing Tian. Qing 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 0
2 0
3 5
4 1
5 3
6 1
7 19
8 0
9 6
10 7
11 2
12 14
13 24
14 2
15 8
16 4
17 1
18 3
19
An adaptive moving least squares method for non-uniform points set fitting
1
20
The theory and application of an adaptive moving least squares for non-uniform samples
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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