Yuanfeng Ji
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence
- Media Technology top 10%
- Industrial and Manufacturing Engineering
- Radiology, Nuclear Medicine and Imaging
- Topics
- Advanced Image and Video Retrieval Techniques (2 papers)Advanced Neural Network Applications (2 papers)Domain Adaptation and Few-Shot Learning (2 papers)
- Cited by
- Computer Vision and Pattern RecognitionMedia TechnologyComputer Graphics and Computer-Aided Design
- Journals
- IEEE Transactions on CyberneticsPolyU Institutional Research Archive (Hong Kong Polytechnic University)Proceedings of the AAAI Conference on Artificial Intelligence
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Yuanfeng Ji
5 papers receiving 205 citations
Peers
Comparison fields: 5 of 48
- Computer Vision and Pattern Recognition 161
- Artificial Intelligence 51
- Media Technology 41
- Industrial and Manufacturing Engineering 17
- Radiology, Nuclear Medicine and Imaging 15
Countries citing papers authored by Yuanfeng Ji
This map shows the geographic impact of Yuanfeng Ji'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 Yuanfeng Ji with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yuanfeng Ji more than expected).
Fields of papers citing papers by Yuanfeng Ji
This network shows the impact of papers produced by Yuanfeng Ji. 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 Yuanfeng Ji. The network helps show where Yuanfeng Ji may publish in the future.
Co-authorship network of co-authors of Yuanfeng Ji
This figure shows the co-authorship network connecting the top 25 collaborators of Yuanfeng Ji. A scholar is included among the top collaborators of Yuanfeng Ji 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 Yuanfeng Ji. Yuanfeng Ji 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 | 19 | |
| 3 | 65 | |
| 4 | RANet: Region attention network for semantic segmentation | 16 |
| 5 | 42 | |
| 6 | 68 |
About Yuanfeng Ji
Yuanfeng Ji is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Theory and Mathematics, having authored 6 papers that have together received 210 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (2 papers), Advanced Neural Network Applications (2 papers) and Domain Adaptation and Few-Shot Learning (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (161 citations), Media Technology (41 citations) and Computer Graphics and Computer-Aided Design (6 citations). Yuanfeng Ji has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Di Lin, Hui Huang, Ping Li, Ruimao Zhang, Ping Luo, Zhe Chen, Zhenguo Li, Lanqing Hong, Xihui Liu and Enze Xie. Their work appears in journals such as IEEE Transactions on Cybernetics, PolyU Institutional Research Archive (Hong Kong Polytechnic University) and Proceedings of the AAAI Conference on Artificial Intelligence.
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.