Yanlu Wei
Impact in
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- Advanced Neural Network Applications
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
Papers in
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- Advanced Neural Network Applications 2
- Advanced Image and Video Retrieval Techniques 1
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- IoT and Edge/Fog Computing 1
- Co-authors
- Xianglong Liu (4 shared papers)Yuqing Ma (3 shared papers)Renshuai Tao (3 shared papers)Libo Zhang (2 shared papers)Hainan Li (1 shared paper)Haotong Qin (1 shared paper)Jiakai Wang (1 shared paper)Sheng Hu (1 shared paper)
- Journals
- Vacuum (1 paper)IEEE Internet of Things Journal (1 paper)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)2021 IEEE/CVF International Conference on Computer Vision (ICCV) (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)
- Partner nations
- China
In The Last Decade
Yanlu Wei
5 papers receiving 329 citations
Peers
Comparison fields: 5 of 52
- Computer Vision and Pattern Recognition 199
- Radiology, Nuclear Medicine and Imaging 101
- Artificial Intelligence 104
- Biomedical Engineering 125
- Electronic, Optical and Magnetic Materials 37
Countries citing papers authored by Yanlu Wei
This map shows the geographic impact of Yanlu Wei'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 Yanlu Wei with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yanlu Wei more than expected).
Fields of papers citing papers by Yanlu Wei
This network shows the impact of papers produced by Yanlu Wei. 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 Yanlu Wei. The network helps show where Yanlu Wei may publish in the future.
Co-authors
The 21 scholars most cited alongside Yanlu Wei, 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 | 2020 | 151 | |
| 2 | 2021 | 83 | |
| 3 | 2020 | 41 | |
| 4 | 2021 | 34 | |
| 5 | 2022 | 29 | |
| 6 | 2025 | 0 |
About Yanlu Wei
Yanlu Wei is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications, Radiology, Nuclear Medicine and Imaging, Biomedical Engineering and Molecular Biology, having authored 6 papers that have together received 338 indexed citations. Recurring topics across this work include Advanced X-ray and CT Imaging (2 papers), Advanced Neural Network Applications (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper), Domain Adaptation and Few-Shot Learning (1 paper), Advanced Image and Video Retrieval Techniques (1 paper), IoT and Edge/Fog Computing (1 paper), Anomaly Detection Techniques and Applications (1 paper) and Ga2O3 and related materials (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (199 citations), Radiology, Nuclear Medicine and Imaging (101 citations), Artificial Intelligence (104 citations), Biomedical Engineering (125 citations) and Electronic, Optical and Magnetic Materials (37 citations). Yanlu Wei has collaborated with scholars based in China. Frequent co-authors include Xianglong Liu, Yuqing Ma, Renshuai Tao, Libo Zhang, Hainan Li, Haotong Qin, Jiakai Wang, Sheng Hu, Jinshi Zhao and Chongbiao Luan. Their work appears in journals such as Vacuum, IEEE Internet of Things Journal, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 IEEE/CVF International Conference on Computer Vision (ICCV) and Proceedings of the AAAI Conference on Artificial 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.