Mathieu Barthet

84 papers receiving 877 citations

Peers

Mathieu Barthet
Comparison fields: 5 of 84
  • Signal Processing 517
  • Human-Computer Interaction 171
  • Computer Vision and Pattern Recognition 598
  • Music 62
  • Cognitive Neuroscience 334
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Kristian Nymoen Norway
Baptiste Caramiaux France
Sergio Canazza Italy
Andrew McPherson United Kingdom
Atau Tanaka United Kingdom
Oliver Bown Australia
Andy Hunt United Kingdom
Anna Xambó United Kingdom
André Holzapfel Spain
Daniel Overholt Denmark
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Citations per field
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Citations per year

Countries citing papers authored by Mathieu Barthet

Since Specialization
Citations

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

Fields of papers citing papers by Mathieu Barthet

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 86 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018175
2 201345
3 201741
4
Multidisciplinary Perspectives on Music Emotion Recognition: Implications for Content and Context-Based Models
201236
5 201835
6 201529
7 201028
8 201027
9 201325
10 201823
11 201322
12 201121
13 201921
14 201820
15 201720
16 201817
17 201316
18 201115
19 202115
20 201613

About Mathieu Barthet

Mathieu Barthet is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Cognitive Neuroscience, Human-Computer Interaction and Artificial Intelligence, having authored 86 papers that have together received 943 indexed citations. Recurring topics across this work include Music Technology and Sound Studies (62 papers), Music and Audio Processing (58 papers), Neuroscience and Music Perception (28 papers), Tactile and Sensory Interactions (10 papers), Interactive and Immersive Displays (9 papers), Innovative Human-Technology Interaction (6 papers), Video Analysis and Summarization (5 papers) and Emotion and Mood Recognition (5 papers). The work is most often cited by research in Signal Processing (517 citations), Human-Computer Interaction (171 citations), Computer Vision and Pattern Recognition (598 citations), Music (62 citations) and Cognitive Neuroscience (334 citations). Mathieu Barthet has collaborated with scholars based in United Kingdom, France and United States. Frequent co-authors include Luca Turchet, György Fazekas, M. Sandler, Carlo Fischione, Georg Essl, Damián Keller, Richard Kronland-Martinet, Sølvi Ystad, Şefki Kolozali and Nick Bryan–Kinns. Their work appears in journals such as Journal of the Audio Engineering Society, IEEE Transactions on Affective Computing, Music Perception An Interdisciplinary Journal, Journal of New Music Research 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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