Fei Pan
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 5%
- Radiology, Nuclear Medicine and Imaging
- Media Technology top 10%
- Atomic and Molecular Physics, and Optics
- Topics
- Quantum Information and Cryptography (6 papers)Domain Adaptation and Few-Shot Learning (5 papers)Quantum Mechanics and Applications (4 papers)
- Journals
- Scientific ReportsSolid State CommunicationsIEEE Transactions on Circuits and Systems for Video Technology
- Partner nations
- ChinaSouth KoreaUnited States
In The Last Decade
Fei Pan
20 papers receiving 391 citations
Hit Papers
Peers
Comparison fields: 5 of 59
- Computer Vision and Pattern Recognition 286
- Artificial Intelligence 247
- Radiology, Nuclear Medicine and Imaging 60
- Media Technology 49
- Atomic and Molecular Physics, and Optics 36
Countries citing papers authored by Fei Pan
This map shows the geographic impact of Fei Pan'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 Fei Pan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fei Pan more than expected).
Fields of papers citing papers by Fei Pan
This network shows the impact of papers produced by Fei Pan. 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 Fei Pan. The network helps show where Fei Pan may publish in the future.
Co-authorship network of co-authors of Fei Pan
This figure shows the co-authorship network connecting the top 25 collaborators of Fei Pan. A scholar is included among the top collaborators of Fei Pan 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 Fei Pan. Fei Pan 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 | 4 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 0 | |
| 7 | 2 | |
| 8 | 0 | |
| 9 | 22 | |
| 10 | Unsupervised Intra-Domain Adaptation for Semantic Segmentation Through Self-Supervisionbreakdown → | 248 |
| 11 | 2 | |
| 12 | 0 | |
| 13 | 39 | |
| 14 | 1 | |
| 15 | 14 | |
| 16 | 0 | |
| 17 | 2 | |
| 18 | 5 | |
| 19 | Rapid and Accurate Density Clustering Analysis for High Dimensional Data. | 1 |
| 20 | 5 |
About Fei Pan
Fei Pan is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Graphics and Computer-Aided Design, having authored 27 papers that have together received 397 indexed citations. Recurring topics across this work include Quantum Information and Cryptography (6 papers), Domain Adaptation and Few-Shot Learning (5 papers) and Quantum Mechanics and Applications (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (286 citations), Artificial Intelligence (247 citations) and Media Technology (49 citations). Fei Pan has collaborated with scholars based in China, South Korea and United States. Frequent co-authors include In So Kweon, Seokju Lee, François Rameau, Inkyu Shin, Liang Qiu, Junsik Kim, Tae-Hyun Oh, Zhi Liu, Yanwen Guo and Yang Zhang. Their work appears in journals such as Scientific Reports, Solid State Communications and IEEE Transactions on Circuits and Systems for Video Technology.
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.