Hang Yu
Impact in
-
- Digital Imaging for Blood Diseases
- Advanced Neural Network Applications
- Health Informatics top 5%
Papers in
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- Digital Imaging for Blood Diseases 8
- Advanced Neural Network Applications 7
- Human Pose and Action Recognition 4
- Advanced Vision and Imaging 4
- Co-authors
- Qingchen ZhangLaurence T. YangDavid ArmstrongM. Jamal DeenStefan JaegerFeng YangRichard J. MaudeZhuo Liu
- Journals
- Future Generation Computer Systems (2 papers)IEEE/ACM Transactions on Computational Biology and Bioinformatics (2 papers)Information Sciences (1 paper)Measurement (1 paper)IEEE Journal of Biomedical and Health Informatics (1 paper)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Hang Yu
56 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 149
- Computer Vision and Pattern Recognition 394
- Health Informatics 26
- Radiology, Nuclear Medicine and Imaging 256
- Artificial Intelligence 333
- Biophysics 57
Countries citing papers authored by Hang Yu
This map shows the geographic impact of Hang 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 Hang Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hang Yu more than expected).
Fields of papers citing papers by Hang Yu
This network shows the impact of papers produced by Hang 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 Hang Yu. The network helps show where Hang Yu may publish in the future.
Co-authors
The 25 scholars most cited alongside Hang 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 | 2025 | 1 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 4 | |
| 5 | 2024 | 1 | |
| 6 | 2023 | 15 | |
| 7 | 2023 | 2 | |
| 8 | 2023 | 8 | |
| 9 | 2023 | 8 | |
| 10 | 2022 | 1 | |
| 11 | 2022 | 11 | |
| 12 | 2021 | 23 | |
| 13 | 2021 | 34 | |
| 14 | 2021 | 0 | |
| 15 | 2020 | 7 | |
| 16 | 2020 | 56 | |
| 17 | 2019 | 43 | |
| 18 | 2019 | 31 | |
| 19 | REDUCING THE DIAGNOSTIC BURDEN OF MALARIA USING MICROSCOPY IMAGE ANALYSIS AND MACHINE LEARNING IN THE FIELD | 2017 | 1 |
| 20 | CRF-based approach to sentence segmentation and punctuation for ancient Chinese prose | 2009 | 2 |
About Hang Yu
Hang Yu is a scholar working on Computational Mathematics, Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design, Artificial Intelligence and Software, having authored 69 papers that have together received 1.1k indexed citations. Recurring topics across this work include Digital Imaging for Blood Diseases (8 papers), COVID-19 diagnosis using AI (8 papers), Advanced Neural Network Applications (7 papers), 3D Shape Modeling and Analysis (5 papers), Mosquito-borne diseases and control (4 papers), Human Pose and Action Recognition (4 papers), Advanced Vision and Imaging (4 papers) and AI in cancer detection (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (394 citations), Health Informatics (26 citations), Radiology, Nuclear Medicine and Imaging (256 citations), Artificial Intelligence (333 citations) and Biophysics (57 citations). Hang Yu has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Qingchen Zhang, Laurence T. Yang, David Armstrong, M. Jamal Deen, Stefan Jaeger, Feng Yang, Richard J. Maude, Zhuo Liu, Taihua Wu and Wenli Dong. Their work appears in journals such as Future Generation Computer Systems, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Information Sciences, Measurement and IEEE Journal of Biomedical and Health Informatics.
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.