Tao Chi
Impact in
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- Advanced Image Processing Techniques
- Image and Signal Denoising Methods
Papers in
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- Energy Efficient Wireless Sensor Networks 3
- Caching and Content Delivery 3
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- Digital Imaging for Blood Diseases 3
- Co-authors
- Kehua Guo (11 shared papers)Y. A. Tang (5 shared papers)Tao Xu (3 shared papers)Jianhua Ma (3 shared papers)Deepak Kumar Jain (1 shared paper)Ming Chen (2 shared papers)Sheng Ren (1 shared paper)Xiaoyan Kui (3 shared papers)
In The Last Decade
Tao Chi
33 papers receiving 327 citations
Peers
Comparison fields: 5 of 100
- Health Informatics 7
- Computer Vision and Pattern Recognition 84
- Biological Psychiatry 9
- Computer Networks and Communications 81
- Media Technology 24
Countries citing papers authored by Tao Chi
This map shows the geographic impact of Tao Chi'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 Tao Chi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tao Chi more than expected).
Fields of papers citing papers by Tao Chi
This network shows the impact of papers produced by Tao Chi. 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 Tao Chi. The network helps show where Tao Chi may publish in the future.
Co-authors
The 25 scholars most cited alongside Tao Chi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 45 | |
| 2 | 2018 | 38 | |
| 3 | 2014 | 30 | |
| 4 | 2017 | 27 | |
| 5 | 2019 | 25 | |
| 6 | 2017 | 22 | |
| 7 | 2008 | 19 | |
| 8 | 2017 | 17 | |
| 9 | 2018 | 17 | |
| 10 | 2018 | 12 | |
| 11 | 2018 | 12 | |
| 12 | 2019 | 12 | |
| 13 | 2024 | 10 | |
| 14 | 2018 | 9 | |
| 15 | 2019 | 9 | |
| 16 | 2019 | 6 | |
| 17 | 2017 | 4 | |
| 18 | 2022 | 3 | |
| 19 | 2010 | 3 | |
| 20 | 2017 | 3 |
About Tao Chi
Tao Chi is a scholar working on Computer Networks and Communications, Computer Vision and Pattern Recognition, Artificial Intelligence, Electrical and Electronic Engineering and Control and Systems Engineering, having authored 36 papers that have together received 341 indexed citations. Recurring topics across this work include AI in cancer detection (4 papers), Digital Imaging for Blood Diseases (3 papers), Metal-Organic Frameworks: Synthesis and Applications (3 papers), Industrial Gas Emission Control (3 papers), Magnetism in coordination complexes (3 papers), Energy Efficient Wireless Sensor Networks (3 papers), Caching and Content Delivery (3 papers) and COVID-19 diagnosis using AI (2 papers). The work is most often cited by research in Health Informatics (7 citations), Computer Vision and Pattern Recognition (84 citations), Biological Psychiatry (9 citations), Computer Networks and Communications (81 citations) and Media Technology (24 citations). Tao Chi has collaborated with scholars based in China, Japan and Norway. Frequent co-authors include Kehua Guo, Y. A. Tang, Tao Xu, Jianhua Ma, Deepak Kumar Jain, Ming Chen, Sheng Ren, Xiaoyan Kui, Zhao‐Xi Wang and Ming Chen. Their work appears in journals such as Ad Hoc Networks, Future Generation Computer Systems, Journal of Network and Computer Applications, Electronics and Signal Processing Image Communication.
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.