Rémi Emonet

1.4k citations
31 papers · 500 indexed · h-index 13

Impact in

Papers in

Rémi Emonet

28 papers receiving 483 citations

Peers

Rémi Emonet
Comparison fields: 5 of 87
  • Computer Vision and Pattern Recognition 262
  • Modeling and Simulation 31
  • Signal Processing 59
  • Artificial Intelligence 174
  • Computational Mathematics 3
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Anum Mehmood China
Muhammad Shahzad Sarfraz Pakistan
Sid Ray Australia
Hans Hauska Sweden
Yiding Yang China
Wallace Casaca Brazil
Chunyang Wu United Kingdom
Zhong Xie China
Baoguo Yu China
Xuke Hu Germany
Rémi Emonet relative to Anum Mehmood China Anum Mehmood's profile →
Citations per field
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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-authorship network

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
#Work
1 20250
2 20232
3 20236
4 202353
5 20223
6 20222
7 20215
8 20214
9 20211
10 202013
11
From Cost-Sensitive to Tight F-measure Bounds
20191
12 20185
13 201465
14 20142
15 20140
16 201325
17 20127
18 201240
19
A Sparsity Constraint for Topic Models - Application to Temporal Activity Mining
20107
20 20061

About Rémi Emonet

Rémi Emonet is a scholar working on Computational Mathematics, Health Informatics, Computer Vision and Pattern Recognition, Modeling and Simulation and Signal Processing, having authored 31 papers that have together received 500 indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (6 papers), Time Series Analysis and Forecasting (5 papers), Human Pose and Action Recognition (5 papers), Video Analysis and Summarization (4 papers), Data-Driven Disease Surveillance (4 papers), Video Surveillance and Tracking Methods (3 papers), COVID-19 epidemiological studies (3 papers) and Complex Network Analysis Techniques (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (262 citations), Modeling and Simulation (31 citations), Signal Processing (59 citations), Artificial Intelligence (174 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, Romain Tavenard, Sébastien Lefèvre, Marc Rußwurm, Élisa Fromont, Devis Tuia and Nicolas Courty. Their work appears in journals such as PLoS ONE, Neurocomputing, Scientific Reports, Water Resources Research and Machine Learning.

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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