Jun Feng
- Computer Networks and Communications top 10%
- Control and Systems Engineering top 10%
- Computational Theory and Mathematics top 5%
- Computer Vision and Pattern Recognition top 10%
- Artificial Intelligence
- Co-authors
- Guoxing WenNing ZhouC. L. Philip ChenBin ZhouWei WeiPeiyi ShenChaoxian ChenHui Chen
- Topics
- Image and Signal Denoising Methods (9 papers)Seismic Imaging and Inversion Techniques (7 papers)Medical Image Segmentation Techniques (4 papers)
- Cited by
- Computational MathematicsComputational Theory and MathematicsComputer Networks and Communications
- Journals
- Earth and Planetary Science LettersIEEE Transactions on Geoscience and Remote SensingInternational Journal of Remote Sensing
- Partner nations
- ChinaUnited StatesTaiwan
In The Last Decade
Jun Feng
24 papers receiving 375 citations
Peers
Comparison fields: 5 of 69
- Computer Networks and Communications 118
- Control and Systems Engineering 93
- Computational Theory and Mathematics 86
- Computer Vision and Pattern Recognition 81
- Artificial Intelligence 80
Countries citing papers authored by Jun Feng
This map shows the geographic impact of Jun Feng'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 Jun Feng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Feng more than expected).
Fields of papers citing papers by Jun Feng
This network shows the impact of papers produced by Jun Feng. 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 Jun Feng. The network helps show where Jun Feng may publish in the future.
Co-authorship network of co-authors of Jun Feng
This figure shows the co-authorship network connecting the top 25 collaborators of Jun Feng. A scholar is included among the top collaborators of Jun Feng 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 Jun Feng. Jun Feng 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 | 0 | |
| 3 | 0 | |
| 4 | 2 | |
| 5 | 2 | |
| 6 | 5 | |
| 7 | 8 | |
| 8 | 4 | |
| 9 | 1 | |
| 10 | 7 | |
| 11 | 5 | |
| 12 | 22 | |
| 13 | 14 | |
| 14 | 13 | |
| 15 | 1 | |
| 16 | 5 | |
| 17 | 152 | |
| 18 | 72 | |
| 19 | 4 | |
| 20 | 3 |
About Jun Feng
Jun Feng is a scholar working on Computational Mathematics, Computer Vision and Pattern Recognition and Media Technology, having authored 28 papers that have together received 376 indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (9 papers), Seismic Imaging and Inversion Techniques (7 papers) and Medical Image Segmentation Techniques (4 papers). The work is most often cited by research in Computational Mathematics (4 citations), Computational Theory and Mathematics (86 citations) and Computer Networks and Communications (118 citations). Jun Feng has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include Guoxing Wen, Ning Zhou, C. L. Philip Chen, Bin Zhou, Wei Wei, Peiyi Shen, Chaoxian Chen, Hui Chen, Xi Liu and Xi Liu. Their work appears in journals such as Earth and Planetary Science Letters, IEEE Transactions on Geoscience and Remote Sensing and International Journal of Remote Sensing.
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.