Yueming Ding
Impact in
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- Multimodal Machine Learning Applications
- Advanced Neural Network Applications
- Advanced Image and Video Retrieval Techniques
- Artificial Intelligence top 10%
- Advanced Technologies in Various Fields
- Domain Adaptation and Few-Shot Learning
Papers in
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- Advanced Image and Video Retrieval Techniques 2
- Video Surveillance and Tracking Methods 2
- Multimodal Machine Learning Applications 2
- Face recognition and analysis 2
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- Domain Adaptation and Few-Shot Learning 2
- Machine Learning and ELM 1
- Machine Learning and Data Classification 1
- Co-authors
- Lirong Yin (3 shared papers)Wenfeng Zheng (3 shared papers)Siyu Lu (2 shared papers)Zhengtong Yin (2 shared papers)Mingzhe Liu (2 shared papers)Jiawei Tian (1 shared paper)Shan Liu (1 shared paper)Tian Xia (1 shared paper)
- Journals
- Multimedia Tools and Applications (1 paper)Applied Sciences (1 paper)International Journal of Computational Intelligence Systems (1 paper)Neural Computing and Applications (1 paper)Applied Energy (1 paper)
- Partner nations
- Hong KongChinaUnited States
In The Last Decade
Yueming Ding
5 papers receiving 268 citations
Yueming Ding's Hit Papers
Peers
Comparison fields: 5 of 100
- Computer Vision and Pattern Recognition 71
- Artificial Intelligence 111
- Management Science and Operations Research 27
- Business and International Management 3
- Health Informatics 2
Countries citing papers authored by Yueming Ding
This map shows the geographic impact of Yueming Ding'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 Yueming Ding with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yueming Ding more than expected).
Fields of papers citing papers by Yueming Ding
This network shows the impact of papers produced by Yueming Ding. 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 Yueming Ding. The network helps show where Yueming Ding may publish in the future.
Co-authors
The 13 scholars most cited alongside Yueming Ding, 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 | Multiscale Feature Extraction and Fusion of Image and Text in VQA Hit paper breakdown → | 2023 | 166 |
| 2 | 2022 | 92 | |
| 3 | 2024 | 9 | |
| 4 | 2023 | 5 | |
| 5 | 2024 | 4 | |
| 6 | 2024 | 1 |
About Yueming Ding
Yueming Ding is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computational Mechanics, Management Science and Operations Research and Electrical and Electronic Engineering, having authored 6 papers that have together received 277 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (2 papers), 3D Shape Modeling and Analysis (2 papers), Video Surveillance and Tracking Methods (2 papers), Multimodal Machine Learning Applications (2 papers), Face recognition and analysis (2 papers), Domain Adaptation and Few-Shot Learning (2 papers), Machine Learning and ELM (1 paper) and Machine Learning and Data Classification (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (71 citations), Artificial Intelligence (111 citations), Management Science and Operations Research (27 citations), Business and International Management (3 citations) and Health Informatics (2 citations). Yueming Ding has collaborated with scholars based in Hong Kong, China and United States. Frequent co-authors include Lirong Yin, Wenfeng Zheng, Siyu Lu, Zhengtong Yin, Mingzhe Liu, Jiawei Tian, Shan Liu, Tian Xia, Bo Yang and P.Y. Mok. Their work appears in journals such as Multimedia Tools and Applications, Applied Sciences, International Journal of Computational Intelligence Systems, Neural Computing and Applications and Applied Energy.
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.