Mathilde Mougeot
Impact in
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- Image and Signal Denoising Methods
- Advanced Data Compression Techniques
- Context-Aware Activity Recognition Systems
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- Neural Networks and Applications
- Domain Adaptation and Few-Shot Learning
- AI in cancer detection
Papers in
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- Anomaly Detection Techniques and Applications 3
- Domain Adaptation and Few-Shot Learning 2
- Machine Learning and Data Classification 2
- Co-authors
- Robert Azencott (3 shared papers)Bernard Angéniol (1 shared paper)Nicolas Vayatis (6 shared papers)Thibault Dairay (3 shared papers)François Deheeger (1 shared paper)Dominique Picard (2 shared papers)Agnès Desolneux (2 shared papers)Serge Muller (1 shared paper)
- Journals
- IEEE Technology and Society Magazine (2 papers)Computer Physics Communications (1 paper)Journal of the Royal Statistical Society Series B (Statistical Methodology) (1 paper)Engineering Applications of Artificial Intelligence (1 paper)Annals of the Institute of Statistical Mathematics (1 paper)
- Partner nations
- FranceUnited StatesCanada
In The Last Decade
Mathilde Mougeot
24 papers receiving 170 citations
Peers
Comparison fields: 5 of 67
- Computer Vision and Pattern Recognition 58
- Artificial Intelligence 65
- Statistical and Nonlinear Physics 23
- Physical Therapy, Sports Therapy and Rehabilitation 8
- Health Informatics 2
Countries citing papers authored by Mathilde Mougeot
This map shows the geographic impact of Mathilde Mougeot'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 Mathilde Mougeot with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mathilde Mougeot more than expected).
Fields of papers citing papers by Mathilde Mougeot
This network shows the impact of papers produced by Mathilde Mougeot. 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 Mathilde Mougeot. The network helps show where Mathilde Mougeot may publish in the future.
Co-authors
The 25 scholars most cited alongside Mathilde Mougeot, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1991 | 42 | |
| 2 | 2022 | 30 | |
| 3 | 2021 | 27 | |
| 4 | 2017 | 19 | |
| 5 | 2021 | 13 | |
| 6 | 2023 | 9 | |
| 7 | 2012 | 6 | |
| 8 | 2016 | 5 | |
| 9 | 2018 | 5 | |
| 10 | 2022 | 4 | |
| 11 | 2020 | 4 | |
| 12 | 2025 | 2 | |
| 13 | 2022 | 2 | |
| 14 | 2023 | 2 | |
| 15 | 2008 | 2 | |
| 16 | 2024 | 1 | |
| 17 | anomaly detection on spectrograms using data-driven and fixed dictionary representations. | 2016 | 1 |
| 18 | 2024 | 1 | |
| 19 | 2011 | 1 | |
| 20 | 2022 | 1 |
About Mathilde Mougeot
Mathilde Mougeot is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Control and Systems Engineering, Statistical and Nonlinear Physics and Computational Mechanics, having authored 32 papers that have together received 181 indexed citations. Recurring topics across this work include Statistical Methods and Inference (3 papers), Anomaly Detection Techniques and Applications (3 papers), Model Reduction and Neural Networks (3 papers), COVID-19 diagnosis using AI (2 papers), Ionosphere and magnetosphere dynamics (2 papers), Financial Risk and Volatility Modeling (2 papers), Domain Adaptation and Few-Shot Learning (2 papers) and Machine Learning and Data Classification (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (58 citations), Artificial Intelligence (65 citations), Statistical and Nonlinear Physics (23 citations), Physical Therapy, Sports Therapy and Rehabilitation (8 citations) and Health Informatics (2 citations). Mathilde Mougeot has collaborated with scholars based in France, United States and Canada. Frequent co-authors include Robert Azencott, Bernard Angéniol, Nicolas Vayatis, Thibault Dairay, François Deheeger, Dominique Picard, Agnès Desolneux, Serge Muller, Riwal Plougonven and Philippe Drobinski. Their work appears in journals such as IEEE Technology and Society Magazine, Computer Physics Communications, Journal of the Royal Statistical Society Series B (Statistical Methodology), Engineering Applications of Artificial Intelligence and Annals of the Institute of Statistical Mathematics.
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.