Dao‐Qing Dai

3.6k citations
116 papers · 2.5k indexed · h-index 30
Topics
Face and Expression Recognition (38 papers)Bioinformatics and Genomic Networks (23 papers)Sparse and Compressive Sensing Techniques (16 papers)
Partner nations
ChinaHong KongAustralia

In The Last Decade

Dao‐Qing Dai

111 papers receiving 2.4k citations

Peers

Dao‐Qing Dai
Comparison fields: 5 of 131
  • Computer Vision and Pattern Recognition 1.4k
  • Artificial Intelligence 518
  • Molecular Biology 504
  • Media Technology 361
  • Signal Processing 349
Replace David L. Neuhoff with:
David L. Neuhoff United States
Jian Lü China
Kwangmoo Koh United States
Marco Cuturi France
David K. Hammond United States
Yi‐Fei Pu China
Zaïd Harchaoui United States
Guangyong Chen China
Enrico Magli Italy
Yiming Ying United States
Dao‐Qing Dai relative to David L. Neuhoff United States David L. Neuhoff's profile →
Citations per field
00.5×3.3×
David L. Neuhoff · 1×
Citations per year

Countries citing papers authored by Dao‐Qing Dai

Since Specialization
Citations

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

Fields of papers citing papers by Dao‐Qing Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dao‐Qing Dai

This figure shows the co-authorship network connecting the top 25 collaborators of Dao‐Qing Dai. A scholar is included among the top collaborators of Dao‐Qing Dai 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 Dao‐Qing Dai. Dao‐Qing Dai 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 6
3 7
4 12
5 13
6 23
7 35
8 57
9 19
10 98
11 34
12 23
13 12
14 10
15 0
16 1
17 37
18 20
19
Local Discriminant Wavelet Packet Coordinates for Face Recognition
34
20 87

About Dao‐Qing Dai

Dao‐Qing Dai is a scholar working on Computer Vision and Pattern Recognition, Applied Mathematics and Media Technology, having authored 116 papers that have together received 2.5k indexed citations. Recurring topics across this work include Face and Expression Recognition (38 papers), Bioinformatics and Genomic Networks (23 papers) and Sparse and Compressive Sensing Techniques (16 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.4k citations), Media Technology (361 citations) and Signal Processing (349 citations). Dao‐Qing Dai has collaborated with scholars based in China, Hong Kong and Australia. Frequent co-authors include Chuan-Xian Ren, Hong Yan, Ke-Kun Huang, Pong C. Yuen, Xiao-Fei Zhang, Zhao‐Rong Lai, Le Ou-Yang, Lixin Shen, Mengyun Wu and Yan-Ran Li. Their work appears in journals such as Bioinformatics, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine Intelligence.

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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