Philippe Pasquier

168 papers receiving 1.9k citations

Peers

Philippe Pasquier
Comparison fields: 5 of 129
  • Human-Computer Interaction 252
  • Computer Vision and Pattern Recognition 696
  • Signal Processing 346
  • Cognitive Neuroscience 392
  • Artificial Intelligence 700
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Denis Lalanne Switzerland
Masanori Sugimoto Japan
George Caridakis Greece
Mubbasir Kapadia United States
Chris Schmandt United States
Bill Kapralos Canada
Derek Brock United States
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Manolya Kavakli Australia
Alexey Karpov Russia
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Citations per year

Countries citing papers authored by Philippe Pasquier

Since Specialization
Citations

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

Fields of papers citing papers by Philippe Pasquier

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 174 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1998198
2 2011100
3 201087
4 201162
5 200356
6 201355
7 202050
8 202048
9 201045
10 201840
11 201840
12 201433
13 201631
14 201931
15
Realtime Generation of Harmonic Progressions Using Constrained Markov Selection.
201030
16
On the benefits of exploiting underlying goals in argument-based negotiation
200729
17 201029
18 201728
19
Argumentation and Persuasion in the Cognitive Coherence Theory
200628
20 201926

About Philippe Pasquier

Philippe Pasquier is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Artificial Intelligence, Cognitive Neuroscience and Control and Systems Engineering, having authored 174 papers that have together received 2.0k indexed citations. Recurring topics across this work include Music Technology and Sound Studies (55 papers), Music and Audio Processing (55 papers), Neuroscience and Music Perception (30 papers), Multi-Agent Systems and Negotiation (29 papers), Human Motion and Animation (15 papers), Human Pose and Action Recognition (12 papers), Video Analysis and Summarization (11 papers) and Artificial Intelligence in Games (10 papers). The work is most often cited by research in Human-Computer Interaction (252 citations), Computer Vision and Pattern Recognition (696 citations), Signal Processing (346 citations), Cognitive Neuroscience (392 citations) and Artificial Intelligence (700 citations). Philippe Pasquier has collaborated with scholars based in Canada, Australia and United States. Frequent co-authors include Arne Eigenfeldt, John Wong-Chung, Hélène Bertrand, Brahim Chaib-draa, Thecla Schiphorst, Liz Sonenberg, Iyad Rahwan, Frank Dignum, Bernhard E. Riecke and Ekaterina R. Stepanova. Their work appears in journals such as Autonomous Agents and Multi-Agent Systems, Journal of New Music Research, Lecture notes in computer science, IEEE Transactions on Computational Intelligence and AI in Games and Journal of the Audio Engineering Society.

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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