Dazhen Deng

650 citations
25 papers · 406 · h-index 10

Impact in

Papers in

Dazhen Deng

21 papers receiving 402 citations

Peers

Dazhen Deng
Comparison fields: 5 of 64
  • Computer Vision and Pattern Recognition 264
  • Signal Processing 58
  • Orthopedics and Sports Medicine 33
  • Economics and Econometrics 88
  • Artificial Intelligence 103
Replace Daniel Seebacher with:
Daniel Seebacher Germany
Adrian Rusu United States
Carlos A. Dietrich Brazil
Alan McCabe United Kingdom
Jan Van Haaren Belgium
Ben Weber United States
Ana Paula Afonso Portugal
David B. Lantrip United States
Danqing Shi China
Sam Snodgrass United States
Dazhen Deng relative to Daniel Seebacher Germany Daniel Seebacher's profile →
Citations per field
00.5×10.7×
Daniel Seebacher · 1×
Citations per year

Countries citing papers authored by Dazhen Deng

Since Specialization
Citations

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

Fields of papers citing papers by Dazhen Deng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Dazhen Deng, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Dazhen Deng Line = papers co-authored together Dazhen Deng links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201886
2 201952
3 202451
4 202044
5 202231
6 202230
7 202219
8 202317
9 202216
10 202313
11 20218
12 20247
13 20247
14 20236
15 20245
16 20244
17 20243
18
VisImages: A Large-scale, High-quality Image Corpus in Visualization Publications.
20203
19 20252
20 20251

About Dazhen Deng

Dazhen Deng is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing, Economics and Econometrics and Ecological Modeling, having authored 25 papers that have together received 406 indexed citations. Recurring topics across this work include Data Visualization and Analytics (13 papers), Video Analysis and Summarization (8 papers), Human Pose and Action Recognition (3 papers), Anomaly Detection Techniques and Applications (3 papers), Sports Analytics and Performance (3 papers), Time Series Analysis and Forecasting (3 papers), Virtual Reality Applications and Impacts (2 papers) and Educational Games and Gamification (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (264 citations), Signal Processing (58 citations), Orthopedics and Sports Medicine (33 citations), Economics and Econometrics (88 citations) and Artificial Intelligence (103 citations). Dazhen Deng has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Yingcai Wu, Xiao Xie, Hui Zhang, Jiachen Wang, Wei Chen, Weiwei Cui, Haidong Zhang, Aoyu Wu, Huamin Qu and Tan Tang. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, IEEE Computer Graphics and Applications, Visual Informatics, Computer Science Review and Singapore Management University Institutional Knowledge (InK) (Singapore Management University).

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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