Charles Bouveyron
- Artificial Intelligence top 2%
- Signal Processing top 5%
- Statistics and Probability top 2%
- Computer Vision and Pattern Recognition top 5%
- Molecular Biology
- Co-authors
- Stéphane GirardJulien JacquesC. SchmidÉtienne CômePierre LatoucheCordelia SchmidLaurent BergéJulie Delon
- Topics
- Bayesian Methods and Mixture Models (28 papers)Advanced Clustering Algorithms Research (20 papers)Face and Expression Recognition (8 papers)
In The Last Decade
Charles Bouveyron
62 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 144
- Artificial Intelligence 746
- Signal Processing 232
- Statistics and Probability 230
- Computer Vision and Pattern Recognition 213
- Molecular Biology 174
Countries citing papers authored by Charles Bouveyron
This map shows the geographic impact of Charles Bouveyron'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 Charles Bouveyron with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Charles Bouveyron more than expected).
Fields of papers citing papers by Charles Bouveyron
This network shows the impact of papers produced by Charles Bouveyron. 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 Charles Bouveyron. The network helps show where Charles Bouveyron may publish in the future.
Co-authorship network of co-authors of Charles Bouveyron
This figure shows the co-authorship network connecting the top 25 collaborators of Charles Bouveyron. A scholar is included among the top collaborators of Charles Bouveyron 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 Charles Bouveyron. Charles Bouveyron 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 | 1 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 3 | |
| 6 | 0 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 8 | |
| 10 | 10 | |
| 11 | 1 | |
| 12 | 6 | |
| 13 | 2 | |
| 14 | Globally Sparse Probabilistic PCA | 4 |
| 15 | 15 | |
| 16 | Statistique en grande dimension : problématiques et enjeux | 1 |
| 17 | 10 | |
| 18 | Classification automatique dans les sous-espaces discriminants de Fisher | 1 |
| 19 | Classification of high dimensional data for cervical cancer detection | 1 |
| 20 | 56 |
About Charles Bouveyron
Charles Bouveyron is a scholar working on Artificial Intelligence, Signal Processing and Statistics and Probability, having authored 70 papers that have together received 1.4k indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (28 papers), Advanced Clustering Algorithms Research (20 papers) and Face and Expression Recognition (8 papers). The work is most often cited by research in Statistics and Probability (230 citations), Artificial Intelligence (746 citations) and Signal Processing (232 citations). Charles Bouveyron has collaborated with scholars based in France, Italy and Ireland. Frequent co-authors include Stéphane Girard, Julien Jacques, C. Schmid, Étienne Côme, Pierre Latouche, Cordelia Schmid, Laurent Bergé, Julie Delon, Laurence Chèze and Juan Sebastián Ulloa. Their work appears in journals such as Scientific Reports, Pattern Recognition and Astronomy and Astrophysics.
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.