Qingyue Wei

1.1k citations
11 papers · 404 indexed · 2 hit papers · h-index 5
Topics
Radiomics and Machine Learning in Medical Imaging (2 papers)Advanced Measurement and Metrology Techniques (2 papers)Advanced Neural Network Applications (2 papers)

In The Last Decade

Qingyue Wei

9 papers receiving 391 citations

Hit Papers

TransUNet: Rethinking the U-Net architecture design for m...20232026202420252024202350100150200250

Peers

Qingyue Wei
Comparison fields: 5 of 78
  • Computer Vision and Pattern Recognition 148
  • Artificial Intelligence 144
  • Radiology, Nuclear Medicine and Imaging 128
  • Neurology 71
  • Biomedical Engineering 51
Replace Hossein Kashiani with:
Hossein Kashiani United States
Haoyu Dong United States
Hanxue Gu United States
Tianbao Zhou China
Jeremiah Neubert United States
Abdelrahman Shaker United Arab Emirates
Junlong Cheng China
Kai Han China
Narinder Singh Punn India
Shuchao Pang China
Qingyue Wei relative to Hossein Kashiani United States Hossein Kashiani's profile →
Citations per field
00.5×3.5×
Hossein Kashiani · 1×
Citations per year

Countries citing papers authored by Qingyue Wei

Since Specialization
Citations

This map shows the geographic impact of Qingyue 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 Qingyue Wei with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qingyue Wei more than expected).

Fields of papers citing papers by Qingyue Wei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Qingyue 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 Qingyue Wei. The network helps show where Qingyue Wei may publish in the future.

Co-authorship network of co-authors of Qingyue Wei

This figure shows the co-authorship network connecting the top 25 collaborators of Qingyue Wei. A scholar is included among the top collaborators of Qingyue Wei 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 Qingyue Wei. Qingyue Wei is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

11 of 11 papers shown
#WorkIndexed citations
1 0
2 2
3 0
4
TransUNet: Rethinking the U-Net architecture design for medical image segmentation through the lens of transformersbreakdown →
287
5 1
6
Label-Efficient Self-Supervised Federated Learning for Tackling Data Heterogeneity in Medical Imagingbreakdown →
89
7 4
8 5
9 1
10 13
11 2

About Qingyue Wei

Qingyue Wei is a scholar working on Radiology, Nuclear Medicine and Imaging, Statistics, Probability and Uncertainty and Computer Vision and Pattern Recognition, having authored 11 papers that have together received 404 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (2 papers), Advanced Measurement and Metrology Techniques (2 papers) and Advanced Neural Network Applications (2 papers). The work is most often cited by research in Neurology (71 citations), Computer Vision and Pattern Recognition (148 citations) and Health Informatics (8 citations). Qingyue Wei has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Yuyin Zhou, Lei Xing, Ehsan Adeli, Le Lü, Alan Yuille, Jieru Mei, Xiangde Luo, Jieneng Chen, Xianhang Li and Yongyi Lu. Their work appears in journals such as IEEE Transactions on Medical Imaging, Medical Image Analysis and Computers in Biology and Medicine.

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.

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