Chi Nhan Duong
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Human-Computer Interaction top 5%
- Experimental and Cognitive Psychology
- Signal Processing
- Co-authors
- Khoa LuuKha Gia QuachNgan LeTien D. BuiMarios SavvidesHan‐Seok SeoThanh-Dat TruongSon Lam Phung
- Topics
- Generative Adversarial Networks and Image Synthesis (7 papers)Face recognition and analysis (7 papers)Advanced Neural Network Applications (7 papers)
- Journals
- IEEE Transactions on Image ProcessingPattern RecognitionInternational Journal of Computer Vision
- Partner nations
- United StatesCanadaVietnam
In The Last Decade
Chi Nhan Duong
24 papers receiving 467 citations
Peers
Comparison fields: 5 of 69
- Computer Vision and Pattern Recognition 360
- Artificial Intelligence 136
- Human-Computer Interaction 65
- Experimental and Cognitive Psychology 40
- Signal Processing 38
Countries citing papers authored by Chi Nhan Duong
This map shows the geographic impact of Chi Nhan Duong'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 Chi Nhan Duong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chi Nhan Duong more than expected).
Fields of papers citing papers by Chi Nhan Duong
This network shows the impact of papers produced by Chi Nhan Duong. 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 Chi Nhan Duong. The network helps show where Chi Nhan Duong may publish in the future.
Co-authorship network of co-authors of Chi Nhan Duong
This figure shows the co-authorship network connecting the top 25 collaborators of Chi Nhan Duong. A scholar is included among the top collaborators of Chi Nhan Duong 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 Chi Nhan Duong. Chi Nhan Duong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 10 | |
| 3 | 63 | |
| 4 | 16 | |
| 5 | 11 | |
| 6 | 47 | |
| 7 | 29 | |
| 8 | 28 | |
| 9 | 4 | |
| 10 | Recognition in Unseen Domains: Domain Generalization via Universal Non-volume Preserving Models. | 2 |
| 11 | 17 | |
| 12 | 17 | |
| 13 | 1 | |
| 14 | 52 | |
| 15 | 39 | |
| 16 | 32 | |
| 17 | 6 | |
| 18 | 24 | |
| 19 | 1 | |
| 20 | 0 |
About Chi Nhan Duong
Chi Nhan Duong is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction and Signal Processing, having authored 25 papers that have together received 477 indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (7 papers), Face recognition and analysis (7 papers) and Advanced Neural Network Applications (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (360 citations), Human-Computer Interaction (65 citations) and Artificial Intelligence (136 citations). Chi Nhan Duong has collaborated with scholars based in United States, Canada and Vietnam. Frequent co-authors include Khoa Luu, Kha Gia Quach, Ngan Le, Tien D. Bui, Marios Savvides, Han‐Seok Seo, Thanh-Dat Truong, Son Lam Phung, Susan Gauch and Xin Li. Their work appears in journals such as IEEE Transactions on Image Processing, Pattern Recognition and International Journal of Computer Vision.
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.