Simiao Yu
Impact in
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- Advanced MRI Techniques and Applications
- Medical Imaging Techniques and Applications
- Radiomics and Machine Learning in Medical Imaging
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- Generative Adversarial Networks and Image Synthesis
- Advanced Image Processing Techniques
Papers in
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- Generative Adversarial Networks and Image Synthesis 2
- Advanced Image and Video Retrieval Techniques 1
- Multimodal Machine Learning Applications 1
- Advanced Image Processing Techniques 1
- Digital Media Forensic Detection 1
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- Advanced X-ray Imaging Techniques 1
- Co-authors
- Hao Dong (3 shared papers)Yike Guo (3 shared papers)Guang Yang (1 shared paper)Fangde Liu (1 shared paper)Greg Slabaugh (1 shared paper)Jennifer Keegan (1 shared paper)Xujiong Ye (1 shared paper)Pier Luigi Dragotti (1 shared paper)
- Journals
- IEEE Transactions on Medical Imaging (1 paper)Rare & Special e-Zone (The Hong Kong University of Science and Technology) (2 papers)
- Partner nations
- United KingdomUnited StatesChina
In The Last Decade
Simiao Yu
3 papers receiving 817 citations
Simiao Yu's Hit Papers
Peers
Comparison fields: 5 of 81
- Radiology, Nuclear Medicine and Imaging 490
- Computer Vision and Pattern Recognition 330
- Computational Mechanics 187
- Acoustics and Ultrasonics 6
- Computer Graphics and Computer-Aided Design 23
Countries citing papers authored by Simiao Yu
This map shows the geographic impact of Simiao Yu'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 Simiao Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Simiao Yu more than expected).
Fields of papers citing papers by Simiao Yu
This network shows the impact of papers produced by Simiao Yu. 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 Simiao Yu. The network helps show where Simiao Yu may publish in the future.
Co-authors
The 12 scholars most cited alongside Simiao Yu, 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 | DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruction Hit paper breakdown → | 2017 | 674 |
| 2 | 2017 | 153 | |
| 3 | 2019 | 7 |
About Simiao Yu
Simiao Yu is a scholar working on Computer Vision and Pattern Recognition, Radiation, Radiology, Nuclear Medicine and Imaging, Infectious Diseases and Organic Chemistry, having authored 3 papers that have together received 834 indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (2 papers), Advanced X-ray Imaging Techniques (1 paper), Advanced Image and Video Retrieval Techniques (1 paper), Medical Imaging Techniques and Applications (1 paper), Advanced MRI Techniques and Applications (1 paper), Multimodal Machine Learning Applications (1 paper), Advanced Image Processing Techniques (1 paper) and Digital Media Forensic Detection (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (490 citations), Computer Vision and Pattern Recognition (330 citations), Computational Mechanics (187 citations), Acoustics and Ultrasonics (6 citations) and Computer Graphics and Computer-Aided Design (23 citations). Simiao Yu has collaborated with scholars based in United Kingdom, United States and China. Frequent co-authors include Hao Dong, Yike Guo, Guang Yang, Fangde Liu, Greg Slabaugh, Jennifer Keegan, Xujiong Ye, Pier Luigi Dragotti, David Firmin and Simon Arridge. Their work appears in journals such as IEEE Transactions on Medical Imaging and Rare & Special e-Zone (The Hong Kong University of Science and 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.