Binh T. Nguyen
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 5%
- Computer Networks and Communications top 10%
- Signal Processing top 10%
- Electrical and Electronic Engineering
- Co-authors
- Cathal GurrinSurasak SanguanpongZubair BaigTrung V. PhanChakchai So–InTri Gia NguyenManh-Duy NguyenHien D. Nguyen
- Topics
- Topic Modeling (14 papers)Multimodal Machine Learning Applications (9 papers)Advanced Image and Video Retrieval Techniques (7 papers)
- Cited by
- Computer Vision and Pattern RecognitionComputer Networks and CommunicationsSignal Processing
- Partner nations
- VietnamIrelandUnited States
In The Last Decade
Binh T. Nguyen
55 papers receiving 490 citations
Peers
Comparison fields: 5 of 93
- Artificial Intelligence 173
- Computer Vision and Pattern Recognition 165
- Computer Networks and Communications 148
- Signal Processing 60
- Electrical and Electronic Engineering 44
Countries citing papers authored by Binh T. Nguyen
This map shows the geographic impact of Binh T. Nguyen'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 Binh T. Nguyen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Binh T. Nguyen more than expected).
Fields of papers citing papers by Binh T. Nguyen
This network shows the impact of papers produced by Binh T. Nguyen. 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 Binh T. Nguyen. The network helps show where Binh T. Nguyen may publish in the future.
Co-authorship network of co-authors of Binh T. Nguyen
This figure shows the co-authorship network connecting the top 25 collaborators of Binh T. Nguyen. A scholar is included among the top collaborators of Binh T. Nguyen 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 Binh T. Nguyen. Binh T. Nguyen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 3 | |
| 7 | 0 | |
| 8 | 0 | |
| 9 | 0 | |
| 10 | 2 | |
| 11 | 7 | |
| 12 | 0 | |
| 13 | 3 | |
| 14 | 13 | |
| 15 | 1 | |
| 16 | 1 | |
| 17 | 4 | |
| 18 | 7 | |
| 19 | 110 | |
| 20 | 10 |
About Binh T. Nguyen
Binh T. Nguyen is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Information Systems, having authored 69 papers that have together received 512 indexed citations. Recurring topics across this work include Topic Modeling (14 papers), Multimodal Machine Learning Applications (9 papers) and Advanced Image and Video Retrieval Techniques (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (165 citations), Computer Networks and Communications (148 citations) and Signal Processing (60 citations). Binh T. Nguyen has collaborated with scholars based in Vietnam, Ireland and United States. Frequent co-authors include Cathal Gurrin, Surasak Sanguanpong, Zubair Baig, Trung V. Phan, Chakchai So–In, Tri Gia Nguyen, Manh-Duy Nguyen, Hien D. Nguyen, Liting Zhou and Denis S. Grebenkov. Their work appears in journals such as PLoS ONE, Scientific Reports and Expert Systems with Applications.
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.