Rémi Emonet

1.4k citations
44 papers · 592 · h-index 14

Impact in

Papers in

Rémi Emonet

38 papers receiving 574 citations

Peers

Rémi Emonet
Comparison fields: 5 of 90
  • Computer Vision and Pattern Recognition 307
  • Signal Processing 77
  • Artificial Intelligence 217
  • Modeling and Simulation 27
  • Computational Mathematics 3
Replace Anum Mehmood with:
Anum Mehmood China
Yiding Yang United States
Sid Ray Australia
Chunyang Wu United Kingdom
Hans Hauska Sweden
Kazuyuki Hara Japan
Baoguo Yu China
Rameswar Debnath Bangladesh
Thomas A. Wettergren United States
Rémi Emonet relative to Anum Mehmood China Anum Mehmood's profile →
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Citations per year

Countries citing papers authored by Rémi Emonet

Since Specialization
Citations

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

Fields of papers citing papers by Rémi Emonet

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Rémi Emonet, 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 Rémi Emonet Line = papers co-authored together Rémi Emonet links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201470
2 200668
3 202359
4 201156
5 201746
6 201242
7 201328
8 201026
9 201321
10 201219
11 201118
12 202016
13 202014
14 201613
15 201613
16 202310
17
A Sparsity Constraint for Topic Models - Application to Temporal Activity Mining
201010
18 20128
19 20215
20 20215

About Rémi Emonet

Rémi Emonet is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing, Statistical and Nonlinear Physics and Epidemiology, having authored 44 papers that have together received 592 indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (9 papers), Human Pose and Action Recognition (6 papers), Time Series Analysis and Forecasting (6 papers), Domain Adaptation and Few-Shot Learning (5 papers), Video Surveillance and Tracking Methods (5 papers), Data-Driven Disease Surveillance (4 papers), Video Analysis and Summarization (4 papers) and COVID-19 epidemiological studies (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (307 citations), Signal Processing (77 citations), Artificial Intelligence (217 citations), Modeling and Simulation (27 citations) and Computational Mathematics (3 citations). Rémi Emonet has collaborated with scholars based in France, Switzerland and United Kingdom. Frequent co-authors include Jean‐Marc Odobez, Jagannadan Varadarajan, Katayoun Farrahi, Manuel Cebrián, Élisa Fromont, Romain Tavenard, Marc Rußwurm, Damien Muselet, Sébastien Lefèvre and Alain Trémeau. Their work appears in journals such as PLoS ONE, International Journal of Computer Vision, Lecture notes in computer science, PLoS Computational Biology and Physical Review Letters.

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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