Guo-Sen Xie
- Computer Vision and Pattern Recognition top 0.5%
- Artificial Intelligence top 1%
- Radiology, Nuclear Medicine and Imaging top 5%
- Media Technology top 1%
- Computational Mechanics top 10%
- Topics
- Domain Adaptation and Few-Shot Learning (39 papers)Multimodal Machine Learning Applications (25 papers)Advanced Neural Network Applications (18 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE Transactions on Pattern Analysis and Machine IntelligenceProceedings of the IEEE
- Partner nations
- ChinaUnited Arab EmiratesAustralia
In The Last Decade
Guo-Sen Xie
75 papers receiving 2.2k citations
Peers
Comparison fields: 5 of 124
- Computer Vision and Pattern Recognition 1.5k
- Artificial Intelligence 1.2k
- Radiology, Nuclear Medicine and Imaging 272
- Media Technology 257
- Computational Mechanics 94
Countries citing papers authored by Guo-Sen Xie
This map shows the geographic impact of Guo-Sen Xie'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 Guo-Sen Xie with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guo-Sen Xie more than expected).
Fields of papers citing papers by Guo-Sen Xie
This network shows the impact of papers produced by Guo-Sen Xie. 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 Guo-Sen Xie. The network helps show where Guo-Sen Xie may publish in the future.
Co-authorship network of co-authors of Guo-Sen Xie
This figure shows the co-authorship network connecting the top 25 collaborators of Guo-Sen Xie. A scholar is included among the top collaborators of Guo-Sen Xie 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 Guo-Sen Xie. Guo-Sen Xie is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 4 | |
| 3 | 2 | |
| 4 | 2 | |
| 5 | 24 | |
| 6 | 3 | |
| 7 | 2 | |
| 8 | 40 | |
| 9 | 7 | |
| 10 | 6 | |
| 11 | 50 | |
| 12 | 22 | |
| 13 | 5 | |
| 14 | 62 | |
| 15 | 26 | |
| 16 | 36 | |
| 17 | 5 | |
| 18 | 33 | |
| 19 | 196 | |
| 20 | 19 |
About Guo-Sen Xie
Guo-Sen Xie is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Sensory Systems, having authored 78 papers that have together received 2.2k indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (39 papers), Multimodal Machine Learning Applications (25 papers) and Advanced Neural Network Applications (18 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.5k citations), Artificial Intelligence (1.2k citations) and Media Technology (257 citations). Guo-Sen Xie has collaborated with scholars based in China, United Arab Emirates and Australia. Frequent co-authors include Ling Shao, Zheng Zhang, Xu-Yao Zhang, Yazhou Yao, Cheng‐Lin Liu, Shuicheng Yan, Huan Xiong, Zhihui Lai, Fumin Shen and Li Liu. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and Proceedings of the IEEE.
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.