Qing Tao

1.7k total citations
88 papers, 1.1k citations indexed

About

Qing Tao is a scholar working on Artificial Intelligence, Computational Mechanics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Qing Tao has authored 88 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Artificial Intelligence, 21 papers in Computational Mechanics and 18 papers in Computer Vision and Pattern Recognition. Recurrent topics in Qing Tao's work include Neural Networks and Applications (14 papers), Sparse and Compressive Sensing Techniques (12 papers) and Face and Expression Recognition (11 papers). Qing Tao is often cited by papers focused on Neural Networks and Applications (14 papers), Sparse and Compressive Sensing Techniques (12 papers) and Face and Expression Recognition (11 papers). Qing Tao collaborates with scholars based in China, United States and Hong Kong. Qing Tao's co-authors include Jue Wang, Jinde Cao, Gaowei Wu, Jue Wang, Zhisong Pan, Feng Wang, Hong Qiao, Xiaoqin Yang, Jinyong Zhang and Dongdong Cao and has published in prestigious journals such as SHILAP Revista de lepidopterología, Chemical Engineering Journal and IEEE Access.

In The Last Decade

Qing Tao

83 papers receiving 1.1k citations

Peers

Qing Tao
Comparison fields: 5 of 109
  • Artificial Intelligence 392
  • Mechanical Engineering 303
  • Computer Vision and Pattern Recognition 278
  • Control and Systems Engineering 186
  • Mechanics of Materials 115
Replace Jinzhu Gao with:
Jinzhu Gao United States
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Jinzhu Gao United States View profile →
Citations per field, relative to Qing Tao
Qing Tao · 1×
Citations per year, relative to Qing Tao
Qing Tao · 1×

Countries citing papers authored by Qing Tao

Since Specialization
Citations

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

Fields of papers citing papers by Qing Tao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qing Tao

This figure shows the co-authorship network connecting the top 25 collaborators of Qing Tao. A scholar is included among the top collaborators of Qing Tao 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 Tao. Qing Tao 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 4
2 1
3 0
4 1
5 1
6 0
7 5
8 1
9 11
10 2
11 1
12 1
13 1
14 6
15
Criticizing the Materialization Phenomenon of Small Class from Human Nature Perspective
1
16 47
17 26
18
STUDY ON THE SORPTION BEHAVIOR OF ATRAZINE BY NATURAL AQUATIC SEDIMENTS
4
19
The Neural Network Model for Solving Minimax Problems with Constraints
11
20 23

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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