Can Cui
Impact in
-
- Autonomous Vehicle Technology and Safety
-
- Advanced Neural Network Applications
- Multimodal Machine Learning Applications
Papers in
-
- AI in cancer detection 2
-
- Autonomous Vehicle Technology and Safety 4
- Co-authors
- Yunsheng Ma (6 shared papers)Ziran Wang (7 shared papers)Wenqian Ye (3 shared papers)Xu Cao (3 shared papers)Juanwu Lu (6 shared papers)Jianzhong Yin (1 shared paper)Na Li (1 shared paper)Wen Shen (2 shared papers)
- Journals
- IEEE Transactions on Intelligent Vehicles (1 paper)Proceedings of the IEEE (1 paper)IEEE Intelligent Transportation Systems Magazine (1 paper)EJNMMI Research (1 paper)International Journal of Gynecology & Obstetrics (1 paper)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Can Cui
18 papers receiving 158 citations
Peers
Comparison fields: 5 of 57
- Automotive Engineering 31
- Computer Vision and Pattern Recognition 41
- Artificial Intelligence 43
- Rheumatology 15
- Building and Construction 15
Countries citing papers authored by Can Cui
This map shows the geographic impact of Can Cui'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 Can Cui with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Can Cui more than expected).
Fields of papers citing papers by Can Cui
This network shows the impact of papers produced by Can Cui. 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 Can Cui. The network helps show where Can Cui may publish in the future.
Co-authors
The 25 scholars most cited alongside Can Cui, 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 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 62 | |
| 2 | 2025 | 18 | |
| 3 | 2023 | 18 | |
| 4 | 2018 | 15 | |
| 5 | 2024 | 11 | |
| 6 | 2023 | 7 | |
| 7 | 2022 | 7 | |
| 8 | 2023 | 5 | |
| 9 | 2022 | 4 | |
| 10 | 2021 | 3 | |
| 11 | 2024 | 2 | |
| 12 | 2024 | 2 | |
| 13 | 2022 | 2 | |
| 14 | Optimization Simulation of XML Performance Based on JSON | 2009 | 1 |
| 15 | 2025 | 1 | |
| 16 | 2025 | 1 | |
| 17 | 2022 | 1 | |
| 18 | 2014 | 1 | |
| 19 | 2026 | 0 | |
| 20 | 2023 | 0 |
About Can Cui
Can Cui is a scholar working on Artificial Intelligence, Automotive Engineering, Computer Vision and Pattern Recognition, Information Systems and Instrumentation, having authored 21 papers that have together received 161 indexed citations. Recurring topics across this work include Autonomous Vehicle Technology and Safety (4 papers), Pelvic floor disorders treatments (2 papers), Advanced Neural Network Applications (2 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Advanced Optical Sensing Technologies (2 papers), AI in cancer detection (2 papers), Brain Tumor Detection and Classification (1 paper) and Blockchain Technology Applications and Security (1 paper). The work is most often cited by research in Automotive Engineering (31 citations), Computer Vision and Pattern Recognition (41 citations), Artificial Intelligence (43 citations), Rheumatology (15 citations) and Building and Construction (15 citations). Can Cui has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Yunsheng Ma, Ziran Wang, Wenqian Ye, Xu Cao, Juanwu Lu, Jianzhong Yin, Na Li, Wen Shen, Yanhong Wu and Yue Cheng. Their work appears in journals such as IEEE Transactions on Intelligent Vehicles, Proceedings of the IEEE, IEEE Intelligent Transportation Systems Magazine, EJNMMI Research and International Journal of Gynecology & Obstetrics.
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.