Quoc-Huy Tran
- Computer Vision and Pattern Recognition top 2%
- Aerospace Engineering top 5%
- Artificial Intelligence
- Media Technology top 10%
- Geology
- Co-authors
- Julio H. ZaragozaDavid SuterTat-Jun ChinMichael S. BrownManmohan ChandrakerM. Zeeshan ZiaGregory D. HagerChi Li
- Topics
- Advanced Vision and Imaging (5 papers)Robotics and Sensor-Based Localization (5 papers)Anomaly Detection Techniques and Applications (4 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
- Partner nations
- United StatesSingaporeAustralia
In The Last Decade
Quoc-Huy Tran
10 papers receiving 465 citations
Hit Papers
Peers
Comparison fields: 5 of 56
- Computer Vision and Pattern Recognition 438
- Aerospace Engineering 207
- Artificial Intelligence 61
- Media Technology 41
- Geology 20
Countries citing papers authored by Quoc-Huy Tran
This map shows the geographic impact of Quoc-Huy Tran'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 Quoc-Huy Tran with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Quoc-Huy Tran more than expected).
Fields of papers citing papers by Quoc-Huy Tran
This network shows the impact of papers produced by Quoc-Huy Tran. 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 Quoc-Huy Tran. The network helps show where Quoc-Huy Tran may publish in the future.
Co-authorship network of co-authors of Quoc-Huy Tran
This figure shows the co-authorship network connecting the top 25 collaborators of Quoc-Huy Tran. A scholar is included among the top collaborators of Quoc-Huy Tran 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 Quoc-Huy Tran. Quoc-Huy Tran 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 | 13 | |
| 4 | 2 | |
| 5 | 27 | |
| 6 | 34 | |
| 7 | 11 | |
| 8 | 58 | |
| 9 | 56 | |
| 10 | 15 | |
| 11 | As-Projective-As-Possible Image Stitching with Moving DLTbreakdown → | 278 |
About Quoc-Huy Tran
Quoc-Huy Tran is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Artificial Intelligence, having authored 11 papers that have together received 497 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (5 papers), Robotics and Sensor-Based Localization (5 papers) and Anomaly Detection Techniques and Applications (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (438 citations), Aerospace Engineering (207 citations) and Media Technology (41 citations). Quoc-Huy Tran has collaborated with scholars based in United States, Singapore and Australia. Frequent co-authors include Julio H. Zaragoza, David Suter, Tat-Jun Chin, Michael S. Brown, Manmohan Chandraker, M. Zeeshan Zia, Gregory D. Hager, Chi Li, Xiang Yu and Bingbing Zhuang. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
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.