Aurélien Mayoue

451 citations
21 papers · 334 · h-index 8

Impact in

Papers in

    • Biometric Identification and Security 6
    • Speech and Audio Processing 4
    • Blind Source Separation Techniques 3
    • Privacy-Preserving Technologies in Data 5
    • Cryptography and Data Security 3
    • Neural Networks and Applications 2

Aurélien Mayoue

20 papers receiving 323 citations

Peers

Aurélien Mayoue
Comparison fields: 5 of 59
  • Signal Processing 175
  • Computer Vision and Pattern Recognition 158
  • Artificial Intelligence 135
  • Information Systems 81
  • Human-Computer Interaction 15
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Citations per year

Countries citing papers authored by Aurélien Mayoue

Since Specialization
Citations

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

Fields of papers citing papers by Aurélien Mayoue

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201183
2 200970
3 202158
4 201237
5 201527
6 200914
7 200811
8 20098
9 20225
10 20244
11 20124
12 20243
13 20232
14 20132
15
From Neuronal cost-based metrics towards sparse coded signals classification
20121
16 20111
17
Apprentissage de Dictionnaires Multivariés et Décomposition Parcimonieuse Invariante par Translation et par Rotation 2D
20111
18 20241
19 20091
20 20091

About Aurélien Mayoue

Aurélien Mayoue is a scholar working on Signal Processing, Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Mechanics and Information Systems, having authored 21 papers that have together received 334 indexed citations. Recurring topics across this work include Biometric Identification and Security (6 papers), Privacy-Preserving Technologies in Data (5 papers), Speech and Audio Processing (4 papers), Blind Source Separation Techniques (3 papers), Cryptography and Data Security (3 papers), Face recognition and analysis (3 papers), Biomedical Text Mining and Ontologies (2 papers) and Neural Networks and Applications (2 papers). The work is most often cited by research in Signal Processing (175 citations), Computer Vision and Pattern Recognition (158 citations), Artificial Intelligence (135 citations), Information Systems (81 citations) and Human-Computer Interaction (15 citations). Aurélien Mayoue has collaborated with scholars based in France, United Kingdom and Switzerland. Frequent co-authors include Bernadette Dorizzi, Sonia Garcia-Salicetti, Nesma Houmani, Cédric Gouy‐Pailler, Oana Mara STAN, Renaud Sirdey, Dario Maio, Matteo Ferrara, Raffaele Cappelli and Davide Maltoni. Their work appears in journals such as IEEE Transactions on Signal Processing, Pattern Recognition, Lecture notes in computer science, IFIP International Federation for Information Processing/IFIP and HAL (Le Centre pour la Communication Scientifique Directe).

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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