Yongsheng Dong
- Computer Vision and Pattern Recognition top 2%
- Media Technology top 2%
- Artificial Intelligence top 10%
- Electrical and Electronic Engineering
- Automotive Engineering top 10%
- Topics
- Advanced Image and Video Retrieval Techniques (23 papers)Advanced Neural Network Applications (19 papers)Image Retrieval and Classification Techniques (12 papers)
- Journals
- IEEE Transactions on Industrial ElectronicsIEEE Transactions on Geoscience and Remote SensingIEEE Transactions on Image Processing
- Partner nations
- ChinaAustraliaUnited Kingdom
In The Last Decade
Yongsheng Dong
50 papers receiving 685 citations
Peers
Comparison fields: 5 of 79
- Computer Vision and Pattern Recognition 397
- Media Technology 208
- Artificial Intelligence 111
- Electrical and Electronic Engineering 88
- Automotive Engineering 84
Countries citing papers authored by Yongsheng Dong
This map shows the geographic impact of Yongsheng 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 Yongsheng Dong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yongsheng Dong more than expected).
Fields of papers citing papers by Yongsheng Dong
This network shows the impact of papers produced by Yongsheng 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 Yongsheng Dong. The network helps show where Yongsheng Dong may publish in the future.
Co-authorship network of co-authors of Yongsheng Dong
This figure shows the co-authorship network connecting the top 25 collaborators of Yongsheng Dong. A scholar is included among the top collaborators of Yongsheng 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 Yongsheng Dong. Yongsheng 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 | 2 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 6 | |
| 5 | 1 | |
| 6 | 23 | |
| 7 | 1 | |
| 8 | 8 | |
| 9 | 20 | |
| 10 | 26 | |
| 11 | 70 | |
| 12 | 10 | |
| 13 | 26 | |
| 14 | 34 | |
| 15 | 48 | |
| 16 | 5 | |
| 17 | 18 | |
| 18 | 29 | |
| 19 | 62 | |
| 20 | 1 |
About Yongsheng Dong
Yongsheng Dong is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Sensory Systems, having authored 58 papers that have together received 700 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (23 papers), Advanced Neural Network Applications (19 papers) and Image Retrieval and Classification Techniques (12 papers). The work is most often cited by research in Media Technology (208 citations), Computer Vision and Pattern Recognition (397 citations) and Computational Mathematics (5 citations). Yongsheng Dong has collaborated with scholars based in China, Australia and United Kingdom. Frequent co-authors include Xuelong Li, Lintao Zheng, Zhumu Fu, Fazhan Tao, Ganchao Liu, Jinwen Ma, Dacheng Tao, Baofeng Ji, Yuan Yuan and Licheng Jiao. Their work appears in journals such as IEEE Transactions on Industrial Electronics, IEEE Transactions on Geoscience and Remote Sensing and IEEE Transactions on Image 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.