Yun Tian
- Information Systems top 1%
- Computer Networks and Communications top 5%
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 5%
- Computational Theory and Mathematics top 5%
- Topics
- Medical Image Segmentation Techniques (20 papers)Cloud Computing and Resource Management (10 papers)Advanced Data Storage Technologies (7 papers)
- Cited by
- Information SystemsComputer Vision and Pattern RecognitionComputer Networks and Communications
- Partner nations
- ChinaUnited StatesSaudi Arabia
In The Last Decade
Yun Tian
81 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 131
- Information Systems 496
- Computer Networks and Communications 420
- Computer Vision and Pattern Recognition 419
- Artificial Intelligence 323
- Computational Theory and Mathematics 178
Countries citing papers authored by Yun Tian
This map shows the geographic impact of Yun Tian'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 Yun Tian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yun Tian more than expected).
Fields of papers citing papers by Yun Tian
This network shows the impact of papers produced by Yun Tian. 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 Yun Tian. The network helps show where Yun Tian may publish in the future.
Co-authorship network of co-authors of Yun Tian
This figure shows the co-authorship network connecting the top 25 collaborators of Yun Tian. A scholar is included among the top collaborators of Yun Tian 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 Yun Tian. Yun Tian 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 | 0 | |
| 3 | 3 | |
| 4 | 6 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 13 | |
| 8 | 1 | |
| 9 | 22 | |
| 10 | Identifying and correcting climate projection biases using artificial intelligence | 2 |
| 11 | 33 | |
| 12 | 1 | |
| 13 | 2 | |
| 14 | 5 | |
| 15 | 63 | |
| 16 | 6 | |
| 17 | 1 | |
| 18 | 11 | |
| 19 | 12 | |
| 20 | Incremental Learning for Interaction Dynamics with the Influence Model | 0 |
About Yun Tian
Yun Tian is a scholar working on Computer Vision and Pattern Recognition, Health Informatics and Computer Graphics and Computer-Aided Design, having authored 87 papers that have together received 1.5k indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (20 papers), Cloud Computing and Resource Management (10 papers) and Advanced Data Storage Technologies (7 papers). The work is most often cited by research in Information Systems (496 citations), Computer Vision and Pattern Recognition (419 citations) and Computer Networks and Communications (420 citations). Yun Tian has collaborated with scholars based in China, United States and Saudi Arabia. Frequent co-authors include Lin Sun, Jiucheng Xu, Xiaojun Ruan, Shu Yin, Zhongke Wu, Fuqing Duan, Mingquan Zhou, Jiong Xie, Xiao Qin and Adam Manzanares. Their work appears in journals such as PLoS ONE, Scientific Reports and IEEE Access.
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.