Émilie Dexter

9 total papers · 635 total citations
2 papers, 291 citations indexed

About

Émilie Dexter is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Biomedical Engineering. According to data from OpenAlex, Émilie Dexter has authored 2 papers receiving a total of 291 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Computer Vision and Pattern Recognition, 1 paper in Artificial Intelligence and 1 paper in Biomedical Engineering. Recurrent topics in Émilie Dexter's work include Human Pose and Action Recognition (2 papers), Advanced Vision and Imaging (1 paper) and Video Analysis and Summarization (1 paper). Émilie Dexter is often cited by papers focused on Human Pose and Action Recognition (2 papers), Advanced Vision and Imaging (1 paper) and Video Analysis and Summarization (1 paper). Émilie Dexter collaborates with scholars based in France and United Arab Emirates. Émilie Dexter's co-authors include Patrick Pérez, Ivan Laptev and Imran N. Junejo and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Émilie Dexter

2 papers receiving 281 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Émilie Dexter 278 116 104 63 24 2 291
Chaolong Li 193 0.7× 74 0.6× 98 0.9× 43 0.7× 11 0.5× 5 254
Ming Shao 265 1.0× 48 0.4× 133 1.3× 27 0.4× 20 0.8× 7 319
Yazan Abu Farha 220 0.8× 60 0.5× 127 1.2× 26 0.4× 25 1.0× 8 299
Nazlı İkizler 306 1.1× 91 0.8× 133 1.3× 55 0.9× 16 0.7× 7 325
Miguel Reyes 211 0.8× 55 0.5× 31 0.3× 107 1.7× 25 1.0× 9 257
Will Price 248 0.9× 20 0.2× 127 1.2× 22 0.3× 22 0.9× 3 290
Guoqiang Wei 191 0.7× 50 0.4× 100 1.0× 17 0.3× 8 0.3× 9 251
Jonathan Munro 251 0.9× 19 0.2× 126 1.2× 22 0.3× 22 0.9× 3 295
Davide Moltisanti 257 0.9× 20 0.2× 131 1.3× 25 0.4× 22 0.9× 8 312
Khamar Basha Shaik 160 0.6× 27 0.2× 44 0.4× 59 0.9× 8 0.3× 6 328

Countries citing papers authored by Émilie Dexter

Since Specialization
Citations

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

Fields of papers citing papers by Émilie Dexter

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Émilie Dexter

This figure shows the co-authorship network connecting the top 25 collaborators of Émilie Dexter. A scholar is included among the top collaborators of Émilie Dexter 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 Émilie Dexter. Émilie Dexter is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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