Vincent Duval

1.5k citations
24 papers · 735 indexed · h-index 11

Impact in

Papers in

Vincent Duval

24 papers receiving 704 citations

Peers

Vincent Duval
Comparison fields: 5 of 62
  • Computer Vision and Pattern Recognition 374
  • Computational Mechanics 368
  • Media Technology 155
  • Mathematical Physics 141
  • Computational Mathematics 6
Replace Chengda Yang with:
Chengda Yang United States
Stamatios Lefkimmiatis Switzerland
Tanja Teuber Germany
Ernie Esser Canada
Greg Ongie United States
M.R. Banham United States
Triet Le United States
Xiao-Guang Lv China
Kanghui Guo United States
S. Ramani Switzerland
Vincent Duval relative to Chengda Yang United States Chengda Yang's profile →
Citations per field
00.5×1.5×2.4×
Chengda Yang · 1×
Citations per year

Countries citing papers authored by Vincent Duval

Since Specialization
Citations

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

Fields of papers citing papers by Vincent Duval

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 20 scholars most cited alongside Vincent Duval, 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 Vincent Duval Line = papers co-authored together Vincent Duval links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20243
2 20232
3 20225
4 20205
5 201946
6 20197
7 201858
8 20186
9 20175
10 20179
11 201728
12 201719
13 201643
14 20162
15 20151
16 20152
17 2014133
18
Utilisation des programmes de calcul pour introduire l'algèbre au collège
20132
19 2011174
20 201033

About Vincent Duval

Vincent Duval is a scholar working on Mathematical Physics, Computational Mechanics, Computer Vision and Pattern Recognition, Modeling and Simulation and Media Technology, having authored 24 papers that have together received 735 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (15 papers), Numerical methods in inverse problems (10 papers), Image and Signal Denoising Methods (7 papers), Microwave Imaging and Scattering Analysis (6 papers), Medical Image Segmentation Techniques (5 papers), Medical Imaging Techniques and Applications (4 papers), Advanced Image Processing Techniques (3 papers) and Photoacoustic and Ultrasonic Imaging (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (374 citations), Computational Mechanics (368 citations), Media Technology (155 citations), Mathematical Physics (141 citations) and Computational Mathematics (6 citations). Vincent Duval has collaborated with scholars based in France, United Kingdom and Switzerland. Frequent co-authors include Gabriel Peyré, Charles‐Alban Deledalle, Joseph Salmon, Jean–François Aujol, Yann Gousseau, Emmanuel Soubies, Antonin Chambolle, Luminita A. Vese, Yohann de Castro and Clarice Poon. Their work appears in journals such as Inverse Problems, Journal of Mathematical Imaging and Vision, SIAM Journal on Imaging Sciences, ESAIM Control Optimisation and Calculus of Variations and SIAM Journal on Numerical Analysis.

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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