Dingdong Yang
Impact in
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- Computer Graphics and Visualization Techniques
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- Generative Adversarial Networks and Image Synthesis
- Multimodal Machine Learning Applications
- Advanced Image and Video Retrieval Techniques
- Video Analysis and Summarization
- Advanced Vision and Imaging
- Advanced Image Processing Techniques
Papers in
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- Generative Adversarial Networks and Image Synthesis 3
- Advanced Image and Video Retrieval Techniques 2
- Multimodal Machine Learning Applications 2
- Image and Signal Denoising Methods 1
- Advanced Image Processing Techniques 1
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- Computer Graphics and Visualization Techniques 1
- Co-authors
- Honglak Lee (3 shared papers)Seunghoon Hong (2 shared papers)Jongwook Choi (2 shared papers)Hongyi Xu (1 shared paper)Zihang Jiang (1 shared paper)Zhongcong Xu (1 shared paper)Jianfeng Zhang (1 shared paper)Guoxian Song (1 shared paper)
- Journals
- Lecture notes in computer science (3 papers)World Journal of Clinical Cases (1 paper)
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Dingdong Yang
6 papers receiving 290 citations
Peers
Comparison fields: 5 of 39
- Computer Graphics and Computer-Aided Design 59
- Computer Vision and Pattern Recognition 266
- Computational Mechanics 37
- Human-Computer Interaction 8
- Artificial Intelligence 36
Countries citing papers authored by Dingdong Yang
This map shows the geographic impact of Dingdong Yang'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 Dingdong Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dingdong Yang more than expected).
Fields of papers citing papers by Dingdong Yang
This network shows the impact of papers produced by Dingdong Yang. 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 Dingdong Yang. The network helps show where Dingdong Yang may publish in the future.
Co-authors
The 19 scholars most cited alongside Dingdong Yang, 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 | 2018 | 233 | |
| 2 | 2023 | 43 | |
| 3 | 2022 | 13 | |
| 4 | 2019 | 7 | |
| 5 | 2024 | 3 | |
| 6 | 2019 | 3 |
About Dingdong Yang
Dingdong Yang is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design, Media Technology, Computational Mechanics and Control and Systems Engineering, having authored 6 papers that have together received 302 indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (3 papers), Advanced Image and Video Retrieval Techniques (2 papers), Multimodal Machine Learning Applications (2 papers), Human Motion and Animation (1 paper), Image and Signal Denoising Methods (1 paper), Anesthesia and Pain Management (1 paper), Advanced Image Processing Techniques (1 paper) and Computer Graphics and Visualization Techniques (1 paper). The work is most often cited by research in Computer Graphics and Computer-Aided Design (59 citations), Computer Vision and Pattern Recognition (266 citations), Computational Mechanics (37 citations), Human-Computer Interaction (8 citations) and Artificial Intelligence (36 citations). Dingdong Yang has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Honglak Lee, Seunghoon Hong, Jongwook Choi, Hongyi Xu, Zihang Jiang, Zhongcong Xu, Jianfeng Zhang, Guoxian Song, Xinchao Wang and Yichun Shi. Their work appears in journals such as Lecture notes in computer science and World Journal of Clinical Cases.
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.