Benjamin Renoust
Impact in
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- Data Visualization and Analytics
- Image Retrieval and Classification Techniques
- Advanced Image and Video Retrieval Techniques
- Generative Adversarial Networks and Image Synthesis
- Face recognition and analysis
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- Complex Network Analysis Techniques
Papers in
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- Data Visualization and Analytics 6
- Generative Adversarial Networks and Image Synthesis 4
- Face recognition and analysis 4
- Video Analysis and Summarization 4
- Human Pose and Action Recognition 2
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- Complex Network Analysis Techniques 9
- Opinion Dynamics and Social Influence 3
- Co-authors
- Yuta Nakashima (4 shared papers)Guy Mélançon (7 shared papers)Noa García (2 shared papers)Shin’ichi Satoh (8 shared papers)Tamara Munzner (1 shared paper)Duy-Dinh Le (3 shared papers)David Auber (1 shared paper)Arnaud Sallaberry (1 shared paper)
In The Last Decade
Benjamin Renoust
20 papers receiving 196 citations
Peers
Comparison fields: 5 of 55
- Computer Vision and Pattern Recognition 125
- Statistical and Nonlinear Physics 43
- Computer Graphics and Computer-Aided Design 10
- Signal Processing 25
- General Social Sciences 7
Countries citing papers authored by Benjamin Renoust
This map shows the geographic impact of Benjamin Renoust'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 Benjamin Renoust with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Benjamin Renoust more than expected).
Fields of papers citing papers by Benjamin Renoust
This network shows the impact of papers produced by Benjamin Renoust. 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 Benjamin Renoust. The network helps show where Benjamin Renoust may publish in the future.
Co-authors
The 25 scholars most cited alongside Benjamin Renoust, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 43 | |
| 2 | 2020 | 29 | |
| 3 | 2019 | 27 | |
| 4 | 2015 | 24 | |
| 5 | 2016 | 18 | |
| 6 | 2019 | 8 | |
| 7 | 2018 | 7 | |
| 8 | 2020 | 6 | |
| 9 | 2023 | 5 | |
| 10 | 2017 | 5 | |
| 11 | 2017 | 5 | |
| 12 | 2021 | 5 | |
| 13 | NII-HITACHI-UIT at TRECVID 2016. | 2016 | 4 |
| 14 | 2016 | 4 | |
| 15 | 2019 | 4 | |
| 16 | 2017 | 3 | |
| 17 | 2013 | 3 | |
| 18 | 2019 | 2 | |
| 19 | 2020 | 2 | |
| 20 | 2024 | 1 |
About Benjamin Renoust
Benjamin Renoust is a scholar working on Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics, Artificial Intelligence, Communication and Atomic and Molecular Physics, and Optics, having authored 24 papers that have together received 205 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (9 papers), Data Visualization and Analytics (6 papers), Generative Adversarial Networks and Image Synthesis (4 papers), Face recognition and analysis (4 papers), Video Analysis and Summarization (4 papers), Opinion Dynamics and Social Influence (3 papers), Quantum many-body systems (2 papers) and Human Pose and Action Recognition (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (125 citations), Statistical and Nonlinear Physics (43 citations), Computer Graphics and Computer-Aided Design (10 citations), Signal Processing (25 citations) and General Social Sciences (7 citations). Benjamin Renoust has collaborated with scholars based in Japan, France and Hong Kong. Frequent co-authors include Yuta Nakashima, Guy Mélançon, Noa García, Shin’ichi Satoh, Tamara Munzner, Duy-Dinh Le, David Auber, Arnaud Sallaberry, Antoine Lambert and Kae Nemoto. Their work appears in journals such as Applied Network Science, Political Analysis, Multimedia Tools and Applications, IEEE Transactions on Multimedia and Physical review. B..
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.