Cheng Da
Impact in
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- Handwritten Text Recognition Techniques
- Advanced Image and Video Retrieval Techniques
- Multimodal Machine Learning Applications
- Image Retrieval and Classification Techniques
- Image Processing and 3D Reconstruction
Papers in
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- Advanced Image and Video Retrieval Techniques 6
- Handwritten Text Recognition Techniques 5
- Multimodal Machine Learning Applications 4
- Image Retrieval and Classification Techniques 3
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- Particle accelerators and beam dynamics 12
- Co-authors
- Peng Wang (2 shared papers)Cong Yao (3 shared papers)Chunhong Pan (5 shared papers)Shiming Xiang (4 shared papers)Caihong Li (6 shared papers)Guanglei Wu (5 shared papers)Gaoming Jiang (6 shared papers)Qi Zheng (2 shared papers)
- Journals
- IEEE Transactions on Applied Superconductivity (6 papers)Chinese Science Bulletin (Chinese Version) (2 papers)Cryogenics (2 papers)International Journal of Modern Physics A (2 papers)Machine Learning (1 paper)
- Partner nations
- ChinaUnited StatesCayman Islands
In The Last Decade
Cheng Da
43 papers receiving 514 citations
Peers
Comparison fields: 5 of 79
- Computer Vision and Pattern Recognition 211
- Soil Science 31
- Plant Science 98
- Agronomy and Crop Science 25
- Media Technology 22
Countries citing papers authored by Cheng Da
This map shows the geographic impact of Cheng Da'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 Cheng Da with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cheng Da more than expected).
Fields of papers citing papers by Cheng Da
This network shows the impact of papers produced by Cheng Da. 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 Cheng Da. The network helps show where Cheng Da may publish in the future.
Co-authors
The 25 scholars most cited alongside Cheng Da, 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 47 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 50 | |
| 2 | 2016 | 40 | |
| 3 | 2017 | 37 | |
| 4 | 2023 | 32 | |
| 5 | 2016 | 31 | |
| 6 | 2022 | 29 | |
| 7 | 2014 | 25 | |
| 8 | 2015 | 24 | |
| 9 | 2019 | 22 | |
| 10 | 2015 | 15 | |
| 11 | 2023 | 15 | |
| 12 | 2014 | 15 | |
| 13 | 2018 | 14 | |
| 14 | 2019 | 14 | |
| 15 | 2021 | 12 | |
| 16 | 2017 | 12 | |
| 17 | 2015 | 11 | |
| 18 | 2019 | 11 | |
| 19 | 2014 | 11 | |
| 20 | 2016 | 9 |
About Cheng Da
Cheng Da is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Biomedical Engineering, Electrical and Electronic Engineering and Soil Science, having authored 47 papers that have together received 534 indexed citations. Recurring topics across this work include Particle accelerators and beam dynamics (12 papers), Superconducting Materials and Applications (12 papers), Particle Accelerators and Free-Electron Lasers (9 papers), Advanced Image and Video Retrieval Techniques (6 papers), Handwritten Text Recognition Techniques (5 papers), Multimodal Machine Learning Applications (4 papers), Image Retrieval and Classification Techniques (3 papers) and Agriculture Sustainability and Environmental Impact (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (211 citations), Soil Science (31 citations), Plant Science (98 citations), Agronomy and Crop Science (25 citations) and Media Technology (22 citations). Cheng Da has collaborated with scholars based in China, United States and Cayman Islands. Frequent co-authors include Peng Wang, Cong Yao, Chunhong Pan, Shiming Xiang, Caihong Li, Guanglei Wu, Gaoming Jiang, Qi Zheng, Cong Yao and Liyue Guo. Their work appears in journals such as IEEE Transactions on Applied Superconductivity, Chinese Science Bulletin (Chinese Version), Cryogenics, International Journal of Modern Physics A and Machine Learning.
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.