Xiao Dong
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 5%
- Biomedical Engineering
- Surgery
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Guoyan ZhengHuaxiang ZhangMiguel Á. González BallesterLei ZhuSteffen SchumannZhiyong ChengJunyang ChenWei Wang
- Topics
- Advanced Image and Video Retrieval Techniques (16 papers)Multimodal Machine Learning Applications (10 papers)Medical Image Segmentation Techniques (7 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE AccessIEEE Transactions on Medical Imaging
- Partner nations
- ChinaSwitzerlandUnited States
In The Last Decade
Xiao Dong
47 papers receiving 739 citations
Peers
Comparison fields: 5 of 105
- Computer Vision and Pattern Recognition 349
- Artificial Intelligence 217
- Biomedical Engineering 140
- Surgery 85
- Radiology, Nuclear Medicine and Imaging 77
Countries citing papers authored by Xiao Dong
This map shows the geographic impact of Xiao Dong'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 Xiao Dong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiao Dong more than expected).
Fields of papers citing papers by Xiao Dong
This network shows the impact of papers produced by Xiao Dong. 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 Xiao Dong. The network helps show where Xiao Dong may publish in the future.
Co-authorship network of co-authors of Xiao Dong
This figure shows the co-authorship network connecting the top 25 collaborators of Xiao Dong. A scholar is included among the top collaborators of Xiao Dong 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 Xiao Dong. Xiao Dong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 1 | |
| 4 | 11 | |
| 5 | 5 | |
| 6 | 9 | |
| 7 | 5 | |
| 8 | 2 | |
| 9 | 11 | |
| 10 | 8 | |
| 11 | 82 | |
| 12 | 17 | |
| 13 | 25 | |
| 14 | 38 | |
| 15 | High-Order Graph Convolutional Recurrent Neural Network: A Deep Learning Framework for Network-Scale Traffic Learning and Forecasting | 32 |
| 16 | 0 | |
| 17 | MiDas: automatic extraction of a common domain of discourse in sleep medicine for multi-center data integration. | 6 |
| 18 | 12 | |
| 19 | 13 | |
| 20 | 5 |
About Xiao Dong
Xiao Dong is a scholar working on Computer Vision and Pattern Recognition, Architecture and Artificial Intelligence, having authored 52 papers that have together received 759 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (16 papers), Multimodal Machine Learning Applications (10 papers) and Medical Image Segmentation Techniques (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (349 citations), Artificial Intelligence (217 citations) and Architecture (10 citations). Xiao Dong has collaborated with scholars based in China, Switzerland and United States. Frequent co-authors include Guoyan Zheng, Huaxiang Zhang, Miguel Á. González Ballester, Lei Zhu, Steffen Schumann, Zhiyong Cheng, Junyang Chen, Wei Wang, Jiande Sun and Feiping Nie. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Access and IEEE Transactions on Medical Imaging.
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.