Stéphane Ragot

533 citations
39 papers · 275 · h-index 8

Impact in

Papers in

Stéphane Ragot

33 papers receiving 259 citations

Peers

Stéphane Ragot
Comparison fields: 5 of 27
  • Signal Processing 199
  • Computer Vision and Pattern Recognition 207
  • Computational Mechanics 67
  • Computer Networks and Communications 46
  • Artificial Intelligence 58
Replace Yutaka Kamamoto with:
Yutaka Kamamoto Japan
Roar Hagen Sweden
Davis Y. Pan United States
Huan-yu Su United States
Adil Benyassine United States
Seyoon Jeong South Korea
U. Mittal United States
Anissa Mokraoui France
J. Linden Sweden
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Stéphane Ragot relative to Yutaka Kamamoto Japan Yutaka Kamamoto's profile →
Citations per field
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Citations per year

Countries citing papers authored by Stéphane Ragot

Since Specialization
Citations

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

Fields of papers citing papers by Stéphane Ragot

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200747
2 201533
3 200730
4 200423
5 200818
6 200215
7
G.711.1: A wideband extension to ITU-T G.711
200810
8 20079
9 20088
10 20178
11 20117
12 20067
13 20206
14 20085
15 20014
16 20114
17 20234
18 20174
19 20034
20 20083

About Stéphane Ragot

Stéphane Ragot is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Computer Networks and Communications, Computational Mechanics and Electrical and Electronic Engineering, having authored 39 papers that have together received 275 indexed citations. Recurring topics across this work include Advanced Data Compression Techniques (28 papers), Speech and Audio Processing (14 papers), Wireless Communication Networks Research (10 papers), Digital Filter Design and Implementation (10 papers), Advanced Wireless Communication Techniques (9 papers), Advanced Adaptive Filtering Techniques (8 papers), Image and Signal Denoising Methods (5 papers) and Advanced Wireless Network Optimization (3 papers). The work is most often cited by research in Signal Processing (199 citations), Computer Vision and Pattern Recognition (207 citations), Computational Mechanics (67 citations), Computer Networks and Communications (46 citations) and Artificial Intelligence (58 citations). Stéphane Ragot has collaborated with scholars based in France, Canada and China. Frequent co-authors include Rémi Lefebvre, B. Bessette, Marc Antonini, Peter Jax, Lei Miao, Mi Suk Lee, Dominique Massaloux, Peter Vary, Alberto Blanc and Do Young ‍Kim. Their work appears in journals such as Journal of the Audio Engineering Society, IEEE Transactions on Information Theory, IEEE Transactions on Communications, IEEE Transactions on Audio Speech and Language Processing and Lecture notes in computer science.

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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