Maoying Qiao

415 citations
20 papers · 280 indexed · h-index 10
Topics
Advanced Image and Video Retrieval Techniques (3 papers)Text and Document Classification Technologies (3 papers)Advanced Graph Neural Networks (3 papers)
Partner nations
AustraliaChinaHong Kong

In The Last Decade

Maoying Qiao

18 papers receiving 275 citations

Peers

Maoying Qiao
Comparison fields: 5 of 73
  • Artificial Intelligence 151
  • Computer Vision and Pattern Recognition 120
  • Molecular Biology 35
  • Statistical and Nonlinear Physics 30
  • Radiology, Nuclear Medicine and Imaging 25
Replace Giuseppe Fiameni with:
Giuseppe Fiameni Italy
Ivica Dimitrovski North Macedonia
Gabriele Lombardi Italy
Samuel G. Fadel Brazil
Amreen Batool South Korea
Peihao Wang United States
L. K. Li China
Débora Corrêa Australia
Maoying Qiao relative to Giuseppe Fiameni Italy Giuseppe Fiameni's profile →
Citations per field
00.5×12×
Giuseppe Fiameni · 1×
Citations per year

Countries citing papers authored by Maoying Qiao

Since Specialization
Citations

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

Fields of papers citing papers by Maoying Qiao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maoying Qiao

This figure shows the co-authorship network connecting the top 25 collaborators of Maoying Qiao. A scholar is included among the top collaborators of Maoying 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 Maoying Qiao. Maoying 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 1
2 0
3 0
4 4
5 9
6 30
7 23
8 11
9 17
10 3
11 16
12 17
13 4
14 1
15 83
16 6
17 17
18 18
19 6
20 14

About Maoying Qiao

Maoying Qiao is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 20 papers that have together received 280 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (3 papers), Text and Document Classification Technologies (3 papers) and Advanced Graph Neural Networks (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (120 citations), Artificial Intelligence (151 citations) and Health Informatics (6 citations). Maoying Qiao has collaborated with scholars based in Australia, China and Hong Kong. Frequent co-authors include Dacheng Tao, Wei Bian, Qiang Li, Jie Lü, Junyu Xuan, Jun Yu, Dadong Wang, Richard Yi Da Xu, Jun Cheng and L. Richard Little. Their work appears in journals such as PLoS ONE, Pattern Recognition and International Journal of Computer Vision.

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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