Thanh-Toan Do
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 5%
- Aerospace Engineering top 10%
- Media Technology top 5%
- Oncology
- Co-authors
- Ngai‐Man CheungTuan HoangTam NguyenIan ReidMinh–Triet TranYiren ZhouTrung-Nghia LeJiaqi Jiang
- Topics
- Advanced Image and Video Retrieval Techniques (22 papers)Multimodal Machine Learning Applications (11 papers)Robotics and Sensor-Based Localization (11 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Image ProcessingIEEE Access
- Partner nations
- AustraliaUnited KingdomSingapore
In The Last Decade
Thanh-Toan Do
48 papers receiving 868 citations
Peers
Comparison fields: 5 of 91
- Computer Vision and Pattern Recognition 608
- Artificial Intelligence 244
- Aerospace Engineering 163
- Media Technology 65
- Oncology 59
Countries citing papers authored by Thanh-Toan Do
This map shows the geographic impact of Thanh-Toan 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 Thanh-Toan Do with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thanh-Toan Do more than expected).
Fields of papers citing papers by Thanh-Toan Do
This network shows the impact of papers produced by Thanh-Toan 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 Thanh-Toan Do. The network helps show where Thanh-Toan Do may publish in the future.
Co-authorship network of co-authors of Thanh-Toan Do
This figure shows the co-authorship network connecting the top 25 collaborators of Thanh-Toan Do. A scholar is included among the top collaborators of Thanh-Toan Do based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Thanh-Toan Do. Thanh-Toan Do is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 3 | |
| 3 | 4 | |
| 4 | 18 | |
| 5 | 1 | |
| 6 | 5 | |
| 7 | 11 | |
| 8 | 18 | |
| 9 | 28 | |
| 10 | 93 | |
| 11 | MirrorNet: Bio-Inspired Adversarial Attack for Camouflaged Object Segmentation | 10 |
| 12 | 40 | |
| 13 | 17 | |
| 14 | 30 | |
| 15 | DeepVQ: A Deep Network Architecture for Vector Quantization | 5 |
| 16 | Real-time monocular object instance 6D pose estimation | 13 |
| 17 | LieNet: Real-time Monocular Object Instance 6D Pose Estimation. | 7 |
| 18 | 12 | |
| 19 | 5 | |
| 20 | 23 |
About Thanh-Toan Do
Thanh-Toan Do is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Aerospace Engineering, having authored 52 papers that have together received 895 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (22 papers), Multimodal Machine Learning Applications (11 papers) and Robotics and Sensor-Based Localization (11 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (608 citations), Geology (58 citations) and Artificial Intelligence (244 citations). Thanh-Toan Do has collaborated with scholars based in Australia, United Kingdom and Singapore. Frequent co-authors include Ngai‐Man Cheung, Tuan Hoang, Tam Nguyen, Ian Reid, Minh–Triet Tran, Yiren Zhou, Trung-Nghia Le, Jiaqi Jiang, Shan Luo and Gustavo Carneiro. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and IEEE Access.
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.