Tuong Do
Impact in
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- Multimodal Machine Learning Applications
- Advanced Image and Video Retrieval Techniques
- Human Pose and Action Recognition
- Advanced Neural Network Applications
- Artificial Intelligence top 10%
- Privacy-Preserving Technologies in Data
- Domain Adaptation and Few-Shot Learning
Papers in
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- Advanced Image and Video Retrieval Techniques 4
- Multimodal Machine Learning Applications 2
- Human Pose and Action Recognition 2
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- Privacy-Preserving Technologies in Data 3
- Domain Adaptation and Few-Shot Learning 3
- Imbalanced Data Classification Techniques 1
- Co-authors
- Quang D. Tran (11 shared papers)Erman Tjiputra (11 shared papers)Anh Nguyen (7 shared papers)Huy Dat Tran (2 shared papers)Thanh-Toan Do (1 shared paper)Huy Q. Tran (1 shared paper)Anh Nguyen (2 shared papers)Hoang Chinh Nguyen (1 shared paper)
- Journals
- IEEE Transactions on Medical Imaging (1 paper)ACM Transactions on Graphics (1 paper)Computational Intelligence and Neuroscience (1 paper)BioTechnologia (1 paper)2022 IEEE Intelligent Vehicles Symposium (IV) (1 paper)
- Partner nations
- United KingdomVietnamTaiwan
In The Last Decade
Tuong Do
14 papers receiving 214 citations
Peers
Comparison fields: 5 of 57
- Computer Vision and Pattern Recognition 111
- Artificial Intelligence 131
- Computational Mathematics 2
- Health Informatics 3
- Neurology 12
Countries citing papers authored by Tuong Do
This map shows the geographic impact of Tuong Do'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 Tuong Do with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tuong Do more than expected).
Fields of papers citing papers by Tuong Do
This network shows the impact of papers produced by Tuong Do. 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 Tuong Do. The network helps show where Tuong Do may publish in the future.
Co-authors
The 21 scholars most cited alongside Tuong Do, 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 | 2022 | 81 | |
| 2 | 2019 | 39 | |
| 3 | 2022 | 34 | |
| 4 | 2022 | 17 | |
| 5 | 2023 | 14 | |
| 6 | 2019 | 6 | |
| 7 | 2023 | 6 | |
| 8 | 2021 | 6 | |
| 9 | 2019 | 4 | |
| 10 | 2024 | 4 | |
| 11 | 2023 | 4 | |
| 12 | 2025 | 1 | |
| 13 | 2024 | 1 | |
| 14 | 2018 | 1 | |
| 15 | 2024 | 0 | |
| 16 | 2025 | 0 |
About Tuong Do
Tuong Do is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Control and Systems Engineering, Signal Processing and Automotive Engineering, having authored 16 papers that have together received 218 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (4 papers), Human Motion and Animation (3 papers), Privacy-Preserving Technologies in Data (3 papers), Domain Adaptation and Few-Shot Learning (3 papers), Multimodal Machine Learning Applications (2 papers), Music and Audio Processing (2 papers), Human Pose and Action Recognition (2 papers) and Imbalanced Data Classification Techniques (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (111 citations), Artificial Intelligence (131 citations), Computational Mathematics (2 citations), Health Informatics (3 citations) and Neurology (12 citations). Tuong Do has collaborated with scholars based in United Kingdom, Vietnam and Taiwan. Frequent co-authors include Quang D. Tran, Erman Tjiputra, Anh Nguyen, Huy Dat Tran, Thanh-Toan Do, Huy Q. Tran, Anh Nguyen, Hoang Chinh Nguyen, Trần Khánh Toàn and Duy Thanh Nguyen. Their work appears in journals such as IEEE Transactions on Medical Imaging, ACM Transactions on Graphics, Computational Intelligence and Neuroscience, BioTechnologia and 2022 IEEE Intelligent Vehicles Symposium (IV).
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.