Benjamin Charlier

15 papers receiving 212 citations

Peers

Benjamin Charlier
Comparison fields: 5 of 66
  • Geometry and Topology 50
  • Ophthalmology 22
  • Statistics and Probability 23
  • Computer Vision and Pattern Recognition 59
  • Computer Graphics and Computer-Aided Design 9
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Maxime Louis France
Alberto F. Goldszal United States
John Melonakos United States
Won Hwa Kim United States
Dinggang Shen United States
Joshua V. Stough United States
Pierre Maurel France
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Citations per year

Countries citing papers authored by Benjamin Charlier

Since Specialization
Citations

This map shows the geographic impact of Benjamin Charlier'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 Charlier with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Benjamin Charlier more than expected).

Fields of papers citing papers by Benjamin Charlier

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Benjamin Charlier. 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 Charlier. The network helps show where Benjamin Charlier may publish in the future.

Co-authors

The 25 scholars most cited alongside Benjamin Charlier, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Benjamin Charlier Line = papers co-authored together Benjamin Charlier links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 202148
2 201742
3 201626
4 201022
5 201917
6 201212
7 201811
8
Dispositifs hybrides, nouvelle perspective pour une pédagogie renouvelée de l’enseignement supérieur
201210
9 20199
10 20178
11 20176
12 20182
13 20172
14 20211
15 20221
16 20250

About Benjamin Charlier

Benjamin Charlier is a scholar working on Geometry and Topology, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Computational Mechanics and Political Science and International Relations, having authored 16 papers that have together received 217 indexed citations. Recurring topics across this work include Morphological variations and asymmetry (8 papers), 3D Shape Modeling and Analysis (5 papers), Medical Image Segmentation Techniques (3 papers), Advanced Neuroimaging Techniques and Applications (3 papers), Retinal Imaging and Analysis (2 papers), Glaucoma and retinal disorders (2 papers), Alzheimer's disease research and treatments (1 paper) and Point processes and geometric inequalities (1 paper). The work is most often cited by research in Geometry and Topology (50 citations), Ophthalmology (22 citations), Statistics and Probability (23 citations), Computer Vision and Pattern Recognition (59 citations) and Computer Graphics and Computer-Aided Design (9 citations). Benjamin Charlier has collaborated with scholars based in France, United States and Canada. Frequent co-authors include François‐Xavier Vialard, Jérémie Bigot, Stanley Durrleman, Jean Feydy, Gabriel Peyré, Maxime Louis, Igor Koval, Nicolas Charon, Alexandre Bône and Karteek Popuri. Their work appears in journals such as Methods in Ecology and Evolution, Journal of Mathematical Imaging and Vision, Frontiers in Neuroscience, Medical Image Analysis and Scientific Reports.

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.

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