Frédéric Guyard
Impact in
- Signal Processing top 2%
- Time Series Analysis and Forecasting
- Artificial Intelligence top 2%
- Anomaly Detection Techniques and Applications
- Data Stream Mining Techniques
Papers in
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- Anomaly Detection Techniques and Applications 3
- Internet Traffic Analysis and Secure E-voting 2
- AI in cancer detection 2
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- Image and Signal Denoising Methods 2
- Image and Video Quality Assessment 2
- Co-authors
- María A. Zuluaga (3 shared papers)Pietro Michiardi (2 shared papers)Michel Barlaud (4 shared papers)Jérémie Sellam (1 shared paper)Bruno Fautrel (1 shared paper)Christophe Hudry (1 shared paper)Laure Gossec (1 shared paper)Violaine Foltz (1 shared paper)
In The Last Decade
Frédéric Guyard
14 papers receiving 748 citations
Frédéric Guyard's Hit Papers
Peers
Comparison fields: 5 of 83
- Signal Processing 329
- Artificial Intelligence 562
- Computer Networks and Communications 381
- Health Informatics 9
- Control and Systems Engineering 130
Countries citing papers authored by Frédéric Guyard
This map shows the geographic impact of Frédéric Guyard'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 Frédéric Guyard with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Frédéric Guyard more than expected).
Fields of papers citing papers by Frédéric Guyard
This network shows the impact of papers produced by Frédéric Guyard. 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 Frédéric Guyard. The network helps show where Frédéric Guyard may publish in the future.
Co-authors
The 24 scholars most cited alongside Frédéric Guyard, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | USAD Hit paper breakdown → | 2020 | 595 |
| 2 | 2018 | 100 | |
| 3 | 2006 | 10 | |
| 4 | 2021 | 10 | |
| 5 | Detection and Comparison of RTP and Skype Traffic and Performance | 2006 | 9 |
| 6 | 2009 | 9 | |
| 7 | 2013 | 8 | |
| 8 | 1997 | 7 | |
| 9 | 2021 | 6 | |
| 10 | 2023 | 5 | |
| 11 | 2021 | 4 | |
| 12 | 2014 | 3 | |
| 13 | 2022 | 1 | |
| 14 | 2023 | 1 |
About Frédéric Guyard
Frédéric Guyard is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications, Signal Processing and Statistical and Nonlinear Physics, having authored 14 papers that have together received 768 indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (3 papers), Time Series Analysis and Forecasting (3 papers), Image and Signal Denoising Methods (2 papers), Internet Traffic Analysis and Secure E-voting (2 papers), Image and Video Quality Assessment (2 papers), Network Traffic and Congestion Control (2 papers), Complex Network Analysis Techniques (2 papers) and AI in cancer detection (2 papers). The work is most often cited by research in Signal Processing (329 citations), Artificial Intelligence (562 citations), Computer Networks and Communications (381 citations), Health Informatics (9 citations) and Control and Systems Engineering (130 citations). Frédéric Guyard has collaborated with scholars based in France, Sweden and Austria. Frequent co-authors include María A. Zuluaga, Pietro Michiardi, Michel Barlaud, Jérémie Sellam, Bruno Fautrel, Christophe Hudry, Laure Gossec, Violaine Foltz, H. Servy and Anna Moltó. Their work appears in journals such as Pattern Recognition, Arthritis Care & Research, European Radiology, Lecture notes in computer science and Annals of Telecommunications.
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.