Bruno Pinaud
- Computer Vision and Pattern Recognition top 5%
- Statistical and Nonlinear Physics top 5%
- Artificial Intelligence
- Signal Processing top 10%
- Computational Theory and Mathematics top 10%
- Co-authors
- Daniel ArchambaultHelen C. PurchaseGuy MélançonFintan McGeeBenoît OtjacquesMohammad GhoniemMaribel FernándezClaude Kirchner
- Topics
- Data Visualization and Analytics (17 papers)Complex Network Analysis Techniques (8 papers)Data Management and Algorithms (5 papers)
- Cited by
- Computer Vision and Pattern RecognitionStatistical and Nonlinear PhysicsComputer Graphics and Computer-Aided Design
- Journals
- SHILAP Revista de lepidopterologíaIEEE Transactions on Visualization and Computer GraphicsComputer Graphics Forum
- Partner nations
- FranceUnited KingdomGermany
In The Last Decade
Bruno Pinaud
26 papers receiving 345 citations
Peers
Comparison fields: 5 of 69
- Computer Vision and Pattern Recognition 250
- Statistical and Nonlinear Physics 103
- Artificial Intelligence 90
- Signal Processing 57
- Computational Theory and Mathematics 48
Countries citing papers authored by Bruno Pinaud
This map shows the geographic impact of Bruno Pinaud'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 Bruno Pinaud with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bruno Pinaud more than expected).
Fields of papers citing papers by Bruno Pinaud
This network shows the impact of papers produced by Bruno Pinaud. 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 Bruno Pinaud. The network helps show where Bruno Pinaud may publish in the future.
Co-authorship network of co-authors of Bruno Pinaud
This figure shows the co-authorship network connecting the top 25 collaborators of Bruno Pinaud. A scholar is included among the top collaborators of Bruno Pinaud 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 Bruno Pinaud. Bruno Pinaud 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 | 4 | |
| 3 | 1 | |
| 4 | Visualizing Mobile Phone Communication Data in Criminal Investigations: the Case of Media Multiplexity | 1 |
| 5 | 4 | |
| 6 | 5 | |
| 7 | 1 | |
| 8 | 67 | |
| 9 | 7 | |
| 10 | 2 | |
| 11 | 2 | |
| 12 | 3 | |
| 13 | 2 | |
| 14 | 2 | |
| 15 | 8 | |
| 16 | 15 | |
| 17 | 26 | |
| 18 | 169 | |
| 19 | 9 | |
| 20 | 8 |
About Bruno Pinaud
Bruno Pinaud is a scholar working on Software, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics, having authored 28 papers that have together received 358 indexed citations. Recurring topics across this work include Data Visualization and Analytics (17 papers), Complex Network Analysis Techniques (8 papers) and Data Management and Algorithms (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (250 citations), Statistical and Nonlinear Physics (103 citations) and Computer Graphics and Computer-Aided Design (22 citations). Bruno Pinaud has collaborated with scholars based in France, United Kingdom and Germany. Frequent co-authors include Daniel Archambault, Helen C. Purchase, Guy Mélançon, Fintan McGee, Benoît Otjacques, Mohammad Ghoniem, Maribel Fernández, Claude Kirchner, Pascale Kuntz and Jonathan L. DuBois. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Visualization and Computer Graphics and Computer Graphics Forum.
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.