Hang Dong
- Computer Vision and Pattern Recognition top 1%
- Media Technology top 1%
- Safety, Risk, Reliability and Quality top 5%
- Aerospace Engineering
- Artificial Intelligence
- Topics
- Advanced Image Processing Techniques (8 papers)Image Enhancement Techniques (7 papers)Robotics and Sensor-Based Localization (6 papers)
- Cited by
- Media TechnologyComputer Vision and Pattern RecognitionSafety, Risk, Reliability and Quality
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Hang Dong
20 papers receiving 893 citations
Hit Papers
Peers
Comparison fields: 5 of 49
- Computer Vision and Pattern Recognition 841
- Media Technology 390
- Safety, Risk, Reliability and Quality 100
- Aerospace Engineering 74
- Artificial Intelligence 25
Countries citing papers authored by Hang Dong
This map shows the geographic impact of Hang 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 Hang Dong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hang Dong more than expected).
Fields of papers citing papers by Hang Dong
This network shows the impact of papers produced by Hang 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 Hang Dong. The network helps show where Hang Dong may publish in the future.
Co-authorship network of co-authors of Hang Dong
This figure shows the co-authorship network connecting the top 25 collaborators of Hang Dong. A scholar is included among the top collaborators of Hang 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 Hang Dong. Hang 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 | 0 | |
| 2 | 8 | |
| 3 | 3 | |
| 4 | 0 | |
| 5 | 2 | |
| 6 | 58 | |
| 7 | 11 | |
| 8 | Multi-Scale Boosted Dehazing Network With Dense Feature Fusionbreakdown → | 645 |
| 9 | 4 | |
| 10 | 38 | |
| 11 | 10 | |
| 12 | Online Multi-Object Tracking with Structural Invariance Constraint. | 6 |
| 13 | 4 | |
| 14 | 12 | |
| 15 | 36 | |
| 16 | Gated fusion network for joint image deblurring and super-resolution | 34 |
| 17 | 4 | |
| 18 | 16 | |
| 19 | 22 | |
| 20 | 10 |
About Hang Dong
Hang Dong is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Instrumentation, having authored 22 papers that have together received 927 indexed citations. Recurring topics across this work include Advanced Image Processing Techniques (8 papers), Image Enhancement Techniques (7 papers) and Robotics and Sensor-Based Localization (6 papers). The work is most often cited by research in Media Technology (390 citations), Computer Vision and Pattern Recognition (841 citations) and Safety, Risk, Reliability and Quality (100 citations). Hang Dong has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Fei Wang, Xinyi Zhang, Ming–Hsuan Yang, Jinshan Pan, Lei Xiang, Zhe Hu, Xinyi Zhang, Zhe Hu, Yu Guo and Timothy D. Barfoot. Their work appears in journals such as IEEE Access, Pattern Recognition and International Journal of Computer Vision.
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.