De Cheng
Impact in
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- Multimodal Machine Learning Applications
- Video Surveillance and Tracking Methods
- Advanced Neural Network Applications
- Image Enhancement Techniques
- Human Pose and Action Recognition
- Advanced Image and Video Retrieval Techniques
- Media Technology top 5%
- Advanced Image Fusion Techniques
Papers in
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- Multimodal Machine Learning Applications 9
- Image Enhancement Techniques 6
- Advanced Image Processing Techniques 6
- Video Surveillance and Tracking Methods 5
- Human Pose and Action Recognition 4
- Advanced Neural Network Applications 3
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- Domain Adaptation and Few-Shot Learning 9
- Co-authors
- Dingwen Zhang (14 shared papers)Nannan Wang (18 shared papers)Xinbo Gao (17 shared papers)Jungong Han (2 shared papers)Junwei Han (4 shared papers)Jingyu Zhou (1 shared paper)Qiang Zhang (2 shared papers)Yi Liu (1 shared paper)
In The Last Decade
De Cheng
31 papers receiving 597 citations
De Cheng's Hit Papers
Peers
Comparison fields: 5 of 68
- Computer Vision and Pattern Recognition 429
- Media Technology 89
- Artificial Intelligence 254
- Safety, Risk, Reliability and Quality 19
- General Dentistry 3
Countries citing papers authored by De Cheng
This map shows the geographic impact of De Cheng'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 De Cheng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites De Cheng more than expected).
Fields of papers citing papers by De Cheng
This network shows the impact of papers produced by De Cheng. 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 De Cheng. The network helps show where De Cheng may publish in the future.
Co-authors
The 25 scholars most cited alongside De Cheng, 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 37 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 73 | |
| 2 | Capsule Networks With Residual Pose Routing Hit paper breakdown → | 2024 | 71 |
| 3 | 2022 | 71 | |
| 4 | 2023 | 52 | |
| 5 | 2022 | 41 | |
| 6 | 2022 | 40 | |
| 7 | 2024 | 35 | |
| 8 | 2022 | 27 | |
| 9 | 2024 | 25 | |
| 10 | 2023 | 23 | |
| 11 | 2024 | 23 | |
| 12 | 2023 | 23 | |
| 13 | 2022 | 17 | |
| 14 | 2024 | 12 | |
| 15 | 2024 | 10 | |
| 16 | 2023 | 9 | |
| 17 | 2024 | 9 | |
| 18 | 2024 | 7 | |
| 19 | 2022 | 7 | |
| 20 | 2025 | 5 |
About De Cheng
De Cheng is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Media Technology and Signal Processing, having authored 37 papers that have together received 606 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (9 papers), Domain Adaptation and Few-Shot Learning (9 papers), Image Enhancement Techniques (6 papers), Advanced Image Processing Techniques (6 papers), COVID-19 diagnosis using AI (5 papers), Video Surveillance and Tracking Methods (5 papers), Human Pose and Action Recognition (4 papers) and Advanced Neural Network Applications (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (429 citations), Media Technology (89 citations), Artificial Intelligence (254 citations), Safety, Risk, Reliability and Quality (19 citations) and General Dentistry (3 citations). De Cheng has collaborated with scholars based in China, Hong Kong and Poland. Frequent co-authors include Dingwen Zhang, Nannan Wang, Xinbo Gao, Jungong Han, Junwei Han, Jingyu Zhou, Qiang Zhang, Yi Liu, Shoukun Xu and Bo Wang. Their work appears in journals such as IEEE Transactions on Circuits and Systems for Video Technology, IEEE Transactions on Image Processing, IEEE Transactions on Multimedia, Pattern Recognition and IEEE Transactions on Neural Networks and Learning Systems.
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.