Xiaodong Qiao

496 citations
25 papers · 363 indexed · h-index 7
Topics
Face and Expression Recognition (3 papers)Text and Document Classification Technologies (3 papers)Natural Language Processing Techniques (3 papers)
Partner nations
ChinaSouth Korea

In The Last Decade

Xiaodong Qiao

20 papers receiving 348 citations

Peers

Xiaodong Qiao
Comparison fields: 5 of 95
  • Artificial Intelligence 114
  • Computer Vision and Pattern Recognition 59
  • Mechanical Engineering 52
  • Control and Systems Engineering 45
  • Civil and Structural Engineering 38
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Citations per field
00.5×
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Citations per year

Countries citing papers authored by Xiaodong Qiao

Since Specialization
Citations

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

Fields of papers citing papers by Xiaodong Qiao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaodong Qiao

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaodong Qiao. A scholar is included among the top collaborators of Xiaodong Qiao 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 Xiaodong Qiao. Xiaodong Qiao 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
#WorkIndexed citations
1 0
2 0
3 0
4 2
5 1
6 0
7 4
8 13
9 35
10
The analytic network processes method & fuzzy cognitive map method in decision making: a comparative study
1
11
Mining Technical Topic Networks from Chinese Patents
1
12 10
13 47
14 200
15
A Novel Approach for Co-occurrence Clustering Analysis: Maximal Frequent Itemset Mining
3
16
[Multi-task least-squares support vector regression machines and their applications in NIR spectral analysis].
2
17
Semi-supervised Least-squares Support Vector Regression Machines ★
16
18 3
19 1
20 5

About Xiaodong Qiao

Xiaodong Qiao is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Media Technology, having authored 25 papers that have together received 363 indexed citations. Recurring topics across this work include Face and Expression Recognition (3 papers), Text and Document Classification Technologies (3 papers) and Natural Language Processing Techniques (3 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (26 citations), Artificial Intelligence (114 citations) and Computational Mathematics (2 citations). Xiaodong Qiao has collaborated with scholars based in China and South Korea. Frequent co-authors include Shuo Xu, Lijun Zhu, Xin An, Lin Li, Lijun Zhu, Junsheng Zhang, Xinyue Zhang, Yunchuan Sun, Lin Li and Jie Gui. Their work appears in journals such as Pattern Recognition Letters, Multimedia Tools and Applications and Personal and Ubiquitous Computing.

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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