Ziteng Cui
Impact in
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- Advanced Neural Network Applications
- Image Enhancement Techniques
- Video Surveillance and Tracking Methods
- Advanced Vision and Imaging
- Advanced Image Processing Techniques
- Media Technology top 10%
Papers in
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- Advanced Neural Network Applications 3
- Image Enhancement Techniques 2
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- Domain Adaptation and Few-Shot Learning 2
- Co-authors
- Tatsuya Harada (4 shared papers)Zenghui Zhang (4 shared papers)Lin Gu (1 shared paper)Guo-Jun Qi (1 shared paper)Shaodi You (1 shared paper)Yu Qiao (1 shared paper)Z. J. Guo (1 shared paper)Hongsheng Li (1 shared paper)
- Journals
- International Journal of Environmental Research and Public Health (1 paper)IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)2021 IEEE/CVF International Conference on Computer Vision (ICCV) (1 paper)
In The Last Decade
Ziteng Cui
8 papers receiving 214 citations
Peers
Comparison fields: 5 of 35
- Computer Vision and Pattern Recognition 174
- Media Technology 37
- Instrumentation 11
- Aerospace Engineering 63
- Industrial and Manufacturing Engineering 25
Countries citing papers authored by Ziteng Cui
This map shows the geographic impact of Ziteng 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 Ziteng Cui with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ziteng Cui more than expected).
Fields of papers citing papers by Ziteng Cui
This network shows the impact of papers produced by Ziteng 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 Ziteng Cui. The network helps show where Ziteng Cui may publish in the future.
Co-authors
The 21 scholars most cited alongside Ziteng 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
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 94 | |
| 2 | 2023 | 87 | |
| 3 | 2024 | 16 | |
| 4 | 2022 | 10 | |
| 5 | 2022 | 5 | |
| 6 | 2021 | 3 | |
| 7 | 2020 | 3 | |
| 8 | 2025 | 2 | |
| 9 | 2025 | 0 |
About Ziteng Cui
Ziteng Cui is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Aerospace Engineering, Civil and Structural Engineering and Atomic and Molecular Physics, and Optics, having authored 9 papers that have together received 220 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (3 papers), Image Enhancement Techniques (2 papers), Domain Adaptation and Few-Shot Learning (2 papers), Impact of Light on Environment and Health (1 paper), Color Science and Applications (1 paper), Remote-Sensing Image Classification (1 paper), Grouting, Rheology, and Soil Mechanics (1 paper) and Robotics and Sensor-Based Localization (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (174 citations), Media Technology (37 citations), Instrumentation (11 citations), Aerospace Engineering (63 citations) and Industrial and Manufacturing Engineering (25 citations). Ziteng Cui has collaborated with scholars based in China, Japan and Hong Kong. Frequent co-authors include Tatsuya Harada, Zenghui Zhang, Lin Gu, Guo-Jun Qi, Shaodi You, Yu Qiao, Z. J. Guo, Hongsheng Li, Han Qiu and Tai Wang. Their work appears in journals such as International Journal of Environmental Research and Public Health, IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, Proceedings of the AAAI Conference on Artificial Intelligence and 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
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.