Fangzhou Mu
- Computer Vision and Pattern Recognition top 5%
- Computer Graphics and Computer-Aided Design top 5%
- Artificial Intelligence
- Neurology
- Molecular Biology
- Co-authors
- Chunyuan LiJianwei YangYong Jae LeeQingyang WuHaotian LiuYuheng LiJianfeng GaoKevin A. Lanham
- Topics
- Advanced Optical Sensing Technologies (3 papers)Generative Adversarial Networks and Image Synthesis (2 papers)Ultrasound Imaging and Elastography (2 papers)
- Cited by
- Computer Graphics and Computer-Aided DesignAcoustics and UltrasonicsComputer Vision and Pattern Recognition
- Journals
- BioinformaticsIEEE Transactions on Pattern Analysis and Machine IntelligenceDevelopmental Biology
- Partner nations
- United StatesChinaSwitzerland
In The Last Decade
Fangzhou Mu
13 papers receiving 342 citations
Hit Papers
Peers
Comparison fields: 5 of 90
- Computer Vision and Pattern Recognition 177
- Computer Graphics and Computer-Aided Design 59
- Artificial Intelligence 44
- Neurology 41
- Molecular Biology 37
Countries citing papers authored by Fangzhou Mu
This map shows the geographic impact of Fangzhou Mu'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 Fangzhou Mu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fangzhou Mu more than expected).
Fields of papers citing papers by Fangzhou Mu
This network shows the impact of papers produced by Fangzhou Mu. 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 Fangzhou Mu. The network helps show where Fangzhou Mu may publish in the future.
Co-authorship network of co-authors of Fangzhou Mu
This figure shows the co-authorship network connecting the top 25 collaborators of Fangzhou Mu. A scholar is included among the top collaborators of Fangzhou Mu 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 Fangzhou Mu. Fangzhou Mu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 10 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 0 | |
| 8 | GLIGEN: Open-Set Grounded Text-to-Image Generationbreakdown → | 213 |
| 9 | 3 | |
| 10 | 25 | |
| 11 | 8 | |
| 12 | 5 | |
| 13 | 5 | |
| 14 | 75 |
About Fangzhou Mu
Fangzhou Mu is a scholar working on Instrumentation, Biophysics and Computer Vision and Pattern Recognition, having authored 14 papers that have together received 351 indexed citations. Recurring topics across this work include Advanced Optical Sensing Technologies (3 papers), Generative Adversarial Networks and Image Synthesis (2 papers) and Ultrasound Imaging and Elastography (2 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (59 citations), Acoustics and Ultrasonics (8 citations) and Computer Vision and Pattern Recognition (177 citations). Fangzhou Mu has collaborated with scholars based in United States, China and Switzerland. Frequent co-authors include Chunyuan Li, Jianwei Yang, Yong Jae Lee, Qingyang Wu, Haotian Liu, Yuheng Li, Jianfeng Gao, Kevin A. Lanham, Jessica Plavicki and Jennifer L. Peters. Their work appears in journals such as Bioinformatics, IEEE Transactions on Pattern Analysis and Machine Intelligence and Developmental Biology.
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.