Thanh-Dat Truong
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Biomedical Engineering
- Radiology, Nuclear Medicine and Imaging
- Ecological Modeling
- Co-authors
- Khoa LuuChi Nhan DuongMinh–Triet TranNgan LeVinh-Tiep NguyenSon Lam PhungHan‐Seok SeoXin Li
- Topics
- Multimodal Machine Learning Applications (7 papers)Advanced Neural Network Applications (5 papers)Domain Adaptation and Few-Shot Learning (5 papers)
- Partner nations
- United StatesVietnamCanada
In The Last Decade
Thanh-Dat Truong
19 papers receiving 222 citations
Peers
Comparison fields: 5 of 70
- Computer Vision and Pattern Recognition 160
- Artificial Intelligence 103
- Biomedical Engineering 18
- Radiology, Nuclear Medicine and Imaging 14
- Ecological Modeling 11
Countries citing papers authored by Thanh-Dat Truong
This map shows the geographic impact of Thanh-Dat Truong'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-Dat Truong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thanh-Dat Truong more than expected).
Fields of papers citing papers by Thanh-Dat Truong
This network shows the impact of papers produced by Thanh-Dat Truong. 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-Dat Truong. The network helps show where Thanh-Dat Truong may publish in the future.
Co-authorship network of co-authors of Thanh-Dat Truong
This figure shows the co-authorship network connecting the top 25 collaborators of Thanh-Dat Truong. A scholar is included among the top collaborators of Thanh-Dat Truong 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-Dat Truong. Thanh-Dat Truong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 3 | |
| 4 | 11 | |
| 5 | 10 | |
| 6 | 16 | |
| 7 | 4 | |
| 8 | 8 | |
| 9 | 47 | |
| 10 | 8 | |
| 11 | 28 | |
| 12 | 11 | |
| 13 | 4 | |
| 14 | Recognition in Unseen Domains: Domain Generalization via Universal Non-volume Preserving Models. | 2 |
| 15 | Vehicle Re-identification with Learned Representation and Spatial Verification and Abnormality Detection with Multi-Adaptive Vehicle Detectors for Traffic Video Analysis | 16 |
| 16 | 12 | |
| 17 | Lifelog Moment Retrieval with Visual Concept Fusion and Text-based Query Expansion. | 4 |
| 18 | 15 | |
| 19 | 9 | |
| 20 | 17 |
About Thanh-Dat Truong
Thanh-Dat Truong is a scholar working on Computer Vision and Pattern Recognition, Ecological Modeling and Artificial Intelligence, having authored 20 papers that have together received 226 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (7 papers), Advanced Neural Network Applications (5 papers) and Domain Adaptation and Few-Shot Learning (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (160 citations), Artificial Intelligence (103 citations) and Ecological Modeling (11 citations). Thanh-Dat Truong has collaborated with scholars based in United States, Vietnam and Canada. Frequent co-authors include Khoa Luu, Chi Nhan Duong, Minh–Triet Tran, Ngan Le, Vinh-Tiep Nguyen, Son Lam Phung, Han‐Seok Seo, Xin Li, Chase Rainwater and Ashley P. G. Dowling. Their work appears in journals such as IEEE Access, International Journal of Computer Vision and Neurocomputing.
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.