Ting Xie
- Artificial Intelligence
- Computer Networks and Communications
- Computer Vision and Pattern Recognition
- Information Systems
- Signal Processing
- Co-authors
- Ruihua LiuVarun ChandolaOliver KennedyShambhu UpadhyayaYujun MaXiaoyan LiTaiping ZhangMin Zhou
- Topics
- Face and Expression Recognition (5 papers)Medical Image Segmentation Techniques (4 papers)Image Retrieval and Classification Techniques (4 papers)
- Cited by
- Health InformaticsComputer Graphics and Computer-Aided DesignComputer Networks and Communications
- Journals
- SHILAP Revista de lepidopterologíaExpert Systems with ApplicationsApplied Surface Science
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Ting Xie
36 papers receiving 270 citations
Peers
Comparison fields: 5 of 108
- Artificial Intelligence 74
- Computer Networks and Communications 58
- Computer Vision and Pattern Recognition 42
- Information Systems 38
- Signal Processing 24
Countries citing papers authored by Ting Xie
This map shows the geographic impact of Ting 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 Ting Xie with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ting Xie more than expected).
Fields of papers citing papers by Ting Xie
This network shows the impact of papers produced by Ting 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 Ting Xie. The network helps show where Ting Xie may publish in the future.
Co-authorship network of co-authors of Ting Xie
This figure shows the co-authorship network connecting the top 25 collaborators of Ting Xie. A scholar is included among the top collaborators of Ting 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 Ting Xie. Ting 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 | 1 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 3 | |
| 7 | 3 | |
| 8 | 6 | |
| 9 | 42 | |
| 10 | 31 | |
| 11 | 4 | |
| 12 | 8 | |
| 13 | 10 | |
| 14 | 17 | |
| 15 | 9 | |
| 16 | 10 | |
| 17 | 3 | |
| 18 | 17 | |
| 19 | 2 | |
| 20 | 2 |
About Ting Xie
Ting Xie is a scholar working on Computer Vision and Pattern Recognition, Health Informatics and Media Technology, having authored 39 papers that have together received 275 indexed citations. Recurring topics across this work include Face and Expression Recognition (5 papers), Medical Image Segmentation Techniques (4 papers) and Image Retrieval and Classification Techniques (4 papers). The work is most often cited by research in Health Informatics (5 citations), Computer Graphics and Computer-Aided Design (11 citations) and Computer Networks and Communications (58 citations). Ting Xie has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Ruihua Liu, Varun Chandola, Oliver Kennedy, Shambhu Upadhyaya, Yujun Ma, Xiaoyan Li, Taiping Zhang, Min Zhou, Kenneth E. Jansen and Mark S. Shephard. Their work appears in journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Applied Surface 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.