Yuchen Fan
- Computer Vision and Pattern Recognition top 0.5%
- Media Technology top 0.5%
- Artificial Intelligence top 10%
- Biomedical Engineering
- Computational Mechanics
- Topics
- Advanced Image Processing Techniques (14 papers)Image and Signal Denoising Methods (8 papers)Image Processing Techniques and Applications (8 papers)
- Cited by
- Media TechnologyComputer Vision and Pattern RecognitionComputer Graphics and Computer-Aided Design
- Partner nations
- ChinaUnited StatesItaly
In The Last Decade
Yuchen Fan
40 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 91
- Computer Vision and Pattern Recognition 1.6k
- Media Technology 772
- Artificial Intelligence 94
- Biomedical Engineering 94
- Computational Mechanics 60
Countries citing papers authored by Yuchen Fan
This map shows the geographic impact of Yuchen Fan'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 Yuchen Fan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yuchen Fan more than expected).
Fields of papers citing papers by Yuchen Fan
This network shows the impact of papers produced by Yuchen Fan. 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 Yuchen Fan. The network helps show where Yuchen Fan may publish in the future.
Co-authorship network of co-authors of Yuchen Fan
This figure shows the co-authorship network connecting the top 25 collaborators of Yuchen Fan. A scholar is included among the top collaborators of Yuchen Fan 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 Yuchen Fan. Yuchen Fan 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 | 1 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 6 | |
| 7 | 8 | |
| 8 | 0 | |
| 9 | 2 | |
| 10 | 13 | |
| 11 | 1 | |
| 12 | 58 | |
| 13 | 6 | |
| 14 | Image Super-Resolution with Non-Local Sparse Attentionbreakdown → | 383 |
| 15 | 7 | |
| 16 | Wide activation for efficient image and video super-resolution | 8 |
| 17 | Wide-activated Deep Residual Networks based Restoration for BPG-compressed Images | 27 |
| 18 | Non-local recurrent network for image restoration | 169 |
| 19 | 2 | |
| 20 | 1 |
About Yuchen Fan
Yuchen Fan is a scholar working on Media Technology, Computer Vision and Pattern Recognition and Industrial and Manufacturing Engineering, having authored 47 papers that have together received 1.9k indexed citations. Recurring topics across this work include Advanced Image Processing Techniques (14 papers), Image and Signal Denoising Methods (8 papers) and Image Processing Techniques and Applications (8 papers). The work is most often cited by research in Media Technology (772 citations), Computer Vision and Pattern Recognition (1.6k citations) and Computer Graphics and Computer-Aided Design (25 citations). Yuchen Fan has collaborated with scholars based in China, United States and Italy. Frequent co-authors include Yuqian Zhou, Yiqun Mei, Thomas S. Huang, Ning Xu, Linjie Yang, Humphrey Shi, Ding Liu, Lichao Huang, Ding Liu and Chen Change Loy. Their work appears in journals such as Nano Letters, Environmental Pollution and Chemosphere.
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.