Mingfu Yan
Impact in
-
- Particle physics theoretical and experimental studies
- Quantum Chromodynamics and Particle Interactions
- Particle Detector Development and Performance
- High-Energy Particle Collisions Research
- Dark Matter and Cosmic Phenomena
-
- Advanced Image Processing Techniques
- Image Enhancement Techniques
- Generative Adversarial Networks and Image Synthesis
Papers in
-
- Generative Adversarial Networks and Image Synthesis 2
- Image and Signal Denoising Methods 1
-
- Computer Graphics and Visualization Techniques 1
- Co-authors
- Jianzhuang Liu (3 shared papers)Shifeng Chen (5 shared papers)Chaoqi Chen (1 shared paper)Yu Bing Dong (1 shared paper)He Zhang (1 shared paper)Liangliang Cao (1 shared paper)Yi Huang (1 shared paper)Shifeng Chen (1 shared paper)
In The Last Decade
Mingfu Yan
7 papers receiving 227 citations
Mingfu Yan's Hit Papers
Peers
Comparison fields: 5 of 37
- Nuclear and High Energy Physics 94
- Computer Vision and Pattern Recognition 78
- Computer Graphics and Computer-Aided Design 9
- Radiation 14
- Media Technology 13
Countries citing papers authored by Mingfu Yan
This map shows the geographic impact of Mingfu Yan'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 Mingfu Yan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mingfu Yan more than expected).
Fields of papers citing papers by Mingfu Yan
This network shows the impact of papers produced by Mingfu Yan. 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 Mingfu Yan. The network helps show where Mingfu Yan may publish in the future.
Co-authors
The 9 scholars most cited alongside Mingfu Yan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | STCF conceptual design report (Volume 1): Physics & detector Hit paper breakdown → | 2023 | 113 |
| 2 | 2024 | 58 | |
| 3 | Diffusion Model-Based Image Editing: A Survey Hit paper breakdown → | 2025 | 38 |
| 4 | 2024 | 15 | |
| 5 | 2024 | 5 | |
| 6 | 2024 | 4 | |
| 7 | 2024 | 1 |
About Mingfu Yan
Mingfu Yan is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design, Safety Research, Artificial Intelligence and Nuclear and High Energy Physics, having authored 7 papers that have together received 234 indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (2 papers), Dark Matter and Cosmic Phenomena (1 paper), Human Motion and Animation (1 paper), Computer Graphics and Visualization Techniques (1 paper), Image and Signal Denoising Methods (1 paper), Domain Adaptation and Few-Shot Learning (1 paper), 3D Shape Modeling and Analysis (1 paper) and Mathematics, Computing, and Information Processing (1 paper). The work is most often cited by research in Nuclear and High Energy Physics (94 citations), Computer Vision and Pattern Recognition (78 citations), Computer Graphics and Computer-Aided Design (9 citations), Radiation (14 citations) and Media Technology (13 citations). Mingfu Yan has collaborated with scholars based in China, Russia and Hong Kong. Frequent co-authors include Jianzhuang Liu, Shifeng Chen, Chaoqi Chen, Yu Bing Dong, He Zhang, Liangliang Cao, Yi Huang, Shifeng Chen and Xiaoxin Chen. Their work appears in journals such as Frontiers of Physics, IEEE Transactions on Multimedia and IEEE Transactions on Pattern Analysis and Machine 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.