Chao Dong
- Computer Vision and Pattern Recognition top 0.05%
- Media Technology top 0.02%
- Biomedical Engineering top 5%
- Radiology, Nuclear Medicine and Imaging top 2%
- Artificial Intelligence top 5%
- Topics
- Advanced Image Processing Techniques (41 papers)Advanced Vision and Imaging (24 papers)Image and Signal Denoising Methods (19 papers)
- Cited by
- Media TechnologyComputer Vision and Pattern RecognitionComputer Graphics and Computer-Aided Design
In The Last Decade
Chao Dong
55 papers receiving 10.5k citations
Hit Papers
Peers
Comparison fields: 5 of 148
- Computer Vision and Pattern Recognition 9.1k
- Media Technology 4.9k
- Biomedical Engineering 603
- Radiology, Nuclear Medicine and Imaging 568
- Artificial Intelligence 453
Countries citing papers authored by Chao Dong
This map shows the geographic impact of Chao 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 Chao Dong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chao Dong more than expected).
Fields of papers citing papers by Chao Dong
This network shows the impact of papers produced by Chao 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 Chao Dong. The network helps show where Chao Dong may publish in the future.
Co-authorship network of co-authors of Chao Dong
This figure shows the co-authorship network connecting the top 25 collaborators of Chao Dong. A scholar is included among the top collaborators of Chao 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 Chao Dong. Chao 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 | 1 | |
| 2 | 0 | |
| 3 | 5 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 0 | |
| 7 | 0 | |
| 8 | 4 | |
| 9 | 2 | |
| 10 | 39 | |
| 11 | 9 | |
| 12 | 12 | |
| 13 | 134 | |
| 14 | 14 | |
| 15 | 36 | |
| 16 | EDVR: Video Restoration With Enhanced Deformable Convolutional Networksbreakdown → | 706 |
| 17 | Trinity of Pixel Enhancement: a Joint Solution for Demosaicking, Denoising and Super-Resolution. | 17 |
| 18 | 62 | |
| 19 | Image Super-Resolution Using Deep Convolutional Networksbreakdown → | 6399 |
| 20 | Study on degradation of methamidophos by Pseudomonas sp. S-2 | 4 |
About Chao Dong
Chao Dong is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Computer Graphics and Computer-Aided Design, having authored 61 papers that have together received 10.8k indexed citations. Recurring topics across this work include Advanced Image Processing Techniques (41 papers), Advanced Vision and Imaging (24 papers) and Image and Signal Denoising Methods (19 papers). The work is most often cited by research in Media Technology (4.9k citations), Computer Vision and Pattern Recognition (9.1k citations) and Computer Graphics and Computer-Aided Design (177 citations). Chao Dong has collaborated with scholars based in China, Hong Kong and Australia. Frequent co-authors include Chen Change Loy, Xiaoou Tang, Kaiming He, Xintao Wang, Yu Qiao, Ying Shan, Liangbin Xie, Ke Yu, Kelvin C. K. Chan and Jinjin Gu. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Scientific Reports and Journal of Colloid and Interface Science.
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.