Xi Shen
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Biomedical Engineering
- Media Technology top 10%
- Co-authors
- Tie‐Qiang LiYongxia ZhouXiuhui WangYuan YuanChi‐Man PunWeihuang LiuXiaodong CunDominique Vaufreydaz
- Topics
- Advanced Neural Network Applications (6 papers)Advanced Image and Video Retrieval Techniques (6 papers)Visual Attention and Saliency Detection (3 papers)
- Cited by
- Computer Vision and Pattern RecognitionArtificial IntelligenceRadiology, Nuclear Medicine and Imaging
- Journals
- PLoS ONEIEEE Transactions on Pattern Analysis and Machine IntelligenceNature Nanotechnology
- Partner nations
- FranceChinaUnited States
In The Last Decade
Xi Shen
19 papers receiving 652 citations
Hit Papers
Peers
Comparison fields: 5 of 96
- Computer Vision and Pattern Recognition 363
- Artificial Intelligence 307
- Radiology, Nuclear Medicine and Imaging 119
- Biomedical Engineering 97
- Media Technology 44
Countries citing papers authored by Xi Shen
This map shows the geographic impact of Xi Shen'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 Xi Shen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xi Shen more than expected).
Fields of papers citing papers by Xi Shen
This network shows the impact of papers produced by Xi Shen. 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 Xi Shen. The network helps show where Xi Shen may publish in the future.
Co-authorship network of co-authors of Xi Shen
This figure shows the co-authorship network connecting the top 25 collaborators of Xi Shen. A scholar is included among the top collaborators of Xi Shen 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 Xi Shen. Xi Shen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 12 | |
| 2 | Designing nanotheranostics with machine learningbreakdown → | 91 |
| 3 | 3 | |
| 4 | 33 | |
| 5 | 83 | |
| 6 | 76 | |
| 7 | 88 | |
| 8 | 3 | |
| 9 | 21 | |
| 10 | 6 | |
| 11 | 53 | |
| 12 | 4 | |
| 13 | Re-ranking for image retrieval and transductive few-shot classification | 16 |
| 14 | 26 | |
| 15 | 2 | |
| 16 | Empirical Bayes Transductive Meta-Learning with Synthetic Gradients | 13 |
| 17 | 130 | |
| 18 | 10 | |
| 19 | 2 |
About Xi Shen
Xi Shen is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Artificial Intelligence, having authored 19 papers that have together received 672 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (6 papers), Advanced Image and Video Retrieval Techniques (6 papers) and Visual Attention and Saliency Detection (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (363 citations), Artificial Intelligence (307 citations) and Radiology, Nuclear Medicine and Imaging (119 citations). Xi Shen has collaborated with scholars based in France, China and United States. Frequent co-authors include Tie‐Qiang Li, Yongxia Zhou, Xiuhui Wang, Yuan Yuan, Chi‐Man Pun, Weihuang Liu, Xiaodong Cun, Dominique Vaufreydaz, James L. Crowley and Lang Rao. Their work appears in journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and Nature Nanotechnology.
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.