Yan Dong
- Computer Vision and Pattern Recognition top 5%
- Industrial and Manufacturing Engineering top 5%
- Media Technology top 5%
- Electrical and Electronic Engineering
- Artificial Intelligence
- Co-authors
- Chunlei LiZhoufeng LiuXingshi HeQingqing ZhangShanliang LiuYongsheng ZhuDongya WuGuangshuai Gao
- Topics
- Industrial Vision Systems and Defect Detection (12 papers)Image Processing Techniques and Applications (12 papers)Visual Attention and Saliency Detection (4 papers)
- Cited by
- Industrial and Manufacturing EngineeringMedia TechnologyComputer Vision and Pattern Recognition
- Partner nations
- ChinaUnited KingdomUnited States
In The Last Decade
Yan Dong
32 papers receiving 356 citations
Peers
Comparison fields: 5 of 67
- Computer Vision and Pattern Recognition 163
- Industrial and Manufacturing Engineering 158
- Media Technology 76
- Electrical and Electronic Engineering 58
- Artificial Intelligence 55
Countries citing papers authored by Yan Dong
This map shows the geographic impact of Yan Dong'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 Yan Dong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yan Dong more than expected).
Fields of papers citing papers by Yan Dong
This network shows the impact of papers produced by Yan Dong. 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 Yan Dong. The network helps show where Yan Dong may publish in the future.
Co-authorship network of co-authors of Yan Dong
This figure shows the co-authorship network connecting the top 25 collaborators of Yan Dong. A scholar is included among the top collaborators of Yan Dong 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 Yan Dong. Yan Dong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 11 | |
| 2 | 6 | |
| 3 | 0 | |
| 4 | 18 | |
| 5 | 32 | |
| 6 | 11 | |
| 7 | 1 | |
| 8 | 30 | |
| 9 | 18 | |
| 10 | 2 | |
| 11 | 2 | |
| 12 | 1 | |
| 13 | 4 | |
| 14 | 19 | |
| 15 | 2 | |
| 16 | 19 | |
| 17 | 1 | |
| 18 | 1 | |
| 19 | 7 | |
| 20 | 58 |
About Yan Dong
Yan Dong is a scholar working on Media Technology, Industrial and Manufacturing Engineering and Computer Vision and Pattern Recognition, having authored 35 papers that have together received 372 indexed citations. Recurring topics across this work include Industrial Vision Systems and Defect Detection (12 papers), Image Processing Techniques and Applications (12 papers) and Visual Attention and Saliency Detection (4 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (158 citations), Media Technology (76 citations) and Computer Vision and Pattern Recognition (163 citations). Yan Dong has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Chunlei Li, Zhoufeng Liu, Xingshi He, Qingqing Zhang, Shanliang Liu, Yongsheng Zhu, Dongya Wu, Guangshuai Gao, Xiaohong Su and Boyang Qu. Their work appears in journals such as IEEE Access, Smart Materials and Structures and Signal Processing.
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.