Puyang Wang
- Computer Vision and Pattern Recognition top 5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Artificial Intelligence top 10%
- Biomedical Engineering
- Media Technology top 10%
- Topics
- Advanced Neural Network Applications (5 papers)Radiomics and Machine Learning in Medical Imaging (3 papers)Sparse and Compressive Sensing Techniques (3 papers)
- Cited by
- Health InformaticsComputer Vision and Pattern RecognitionRadiology, Nuclear Medicine and Imaging
- Journals
- IEEE Transactions on Medical ImagingIEEE Journal of Selected Topics in Signal ProcessingLecture notes in computer science
- Partner nations
- United StatesChinaNetherlands
In The Last Decade
Puyang Wang
13 papers receiving 468 citations
Hit Papers
Peers
Comparison fields: 5 of 65
- Computer Vision and Pattern Recognition 213
- Radiology, Nuclear Medicine and Imaging 200
- Artificial Intelligence 167
- Biomedical Engineering 73
- Media Technology 49
Countries citing papers authored by Puyang Wang
This map shows the geographic impact of Puyang Wang'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 Puyang Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Puyang Wang more than expected).
Fields of papers citing papers by Puyang Wang
This network shows the impact of papers produced by Puyang Wang. 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 Puyang Wang. The network helps show where Puyang Wang may publish in the future.
Co-authorship network of co-authors of Puyang Wang
This figure shows the co-authorship network connecting the top 25 collaborators of Puyang Wang. A scholar is included among the top collaborators of Puyang Wang 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 Puyang Wang. Puyang Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | LViT: Language Meets Vision Transformer in Medical Image Segmentationbreakdown → | 135 |
| 3 | 37 | |
| 4 | 111 | |
| 5 | 23 | |
| 6 | 15 | |
| 7 | 22 | |
| 8 | 12 | |
| 9 | 6 | |
| 10 | 58 | |
| 11 | 10 | |
| 12 | 1 | |
| 13 | 39 |
About Puyang Wang
Puyang Wang is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Neurology, having authored 13 papers that have together received 475 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (5 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Sparse and Compressive Sensing Techniques (3 papers). The work is most often cited by research in Health Informatics (31 citations), Computer Vision and Pattern Recognition (213 citations) and Radiology, Nuclear Medicine and Imaging (200 citations). Puyang Wang has collaborated with scholars based in United States, China and Netherlands. Frequent co-authors include Vishal M. Patel, Pengfei Guo, Shanshan Jiang, Jinyuan Zhou, Le Lü, Dazhou Guo, Dakai Jin, Yunxiang Li, Qingde Li and You Zhang. Their work appears in journals such as IEEE Transactions on Medical Imaging, IEEE Journal of Selected Topics in Signal Processing and Lecture notes in computer science.
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.