Zhenyun Deng
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 10%
- Information Systems top 10%
- Computer Networks and Communications top 10%
- Electrical and Electronic Engineering
- Co-authors
- Shichao ZhangDebo ChengMing ZongXiaoshu ZhuXuelian DengRongyao HuXiaofeng ZhuMichael Witbrock
- Topics
- Face and Expression Recognition (6 papers)Advanced Graph Neural Networks (4 papers)Sparse and Compressive Sensing Techniques (3 papers)
- Cited by
- Artificial IntelligenceHealth Information ManagementComputer Vision and Pattern Recognition
- Partner nations
- ChinaNew ZealandAustralia
In The Last Decade
Zhenyun Deng
15 papers receiving 685 citations
Hit Papers
Peers
Comparison fields: 5 of 136
- Artificial Intelligence 312
- Computer Vision and Pattern Recognition 139
- Information Systems 90
- Computer Networks and Communications 74
- Electrical and Electronic Engineering 57
Countries citing papers authored by Zhenyun Deng
This map shows the geographic impact of Zhenyun 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 Zhenyun Deng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zhenyun Deng more than expected).
Fields of papers citing papers by Zhenyun Deng
This network shows the impact of papers produced by Zhenyun 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 Zhenyun Deng. The network helps show where Zhenyun Deng may publish in the future.
Co-authorship network of co-authors of Zhenyun Deng
This figure shows the co-authorship network connecting the top 25 collaborators of Zhenyun Deng. A scholar is included among the top collaborators of Zhenyun Deng 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 Zhenyun Deng. Zhenyun Deng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 8 | |
| 3 | 5 | |
| 4 | 7 | |
| 5 | 1 | |
| 6 | 0 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 0 | |
| 10 | 9 | |
| 11 | 17 | |
| 12 | 19 | |
| 13 | 192 | |
| 14 | 2 | |
| 15 | Efficient kNN classification algorithm for big databreakdown → | 430 |
| 16 | 10 | |
| 17 | 4 |
About Zhenyun Deng
Zhenyun Deng is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology, having authored 17 papers that have together received 707 indexed citations. Recurring topics across this work include Face and Expression Recognition (6 papers), Advanced Graph Neural Networks (4 papers) and Sparse and Compressive Sensing Techniques (3 papers). The work is most often cited by research in Artificial Intelligence (312 citations), Health Information Management (39 citations) and Computer Vision and Pattern Recognition (139 citations). Zhenyun Deng has collaborated with scholars based in China, New Zealand and Australia. Frequent co-authors include Shichao Zhang, Debo Cheng, Ming Zong, Xiaoshu Zhu, Xuelian Deng, Rongyao Hu, Xiaofeng Zhu, Michael Witbrock, Yonghua Zhu and Yang Chen. Their work appears in journals such as Neurocomputing, Pattern Recognition Letters and Neural Computing and Applications.
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.