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Researcher · Sony Computer Science Laboratories · Japan

François Pachet

François Pachet publishes mostly in Signal Processing, Computer Vision and Pattern Recognition and Artificial Intelligence, on topics such as Music Technology and Sound Studies, Music and Audio Processing and Neuroscience and Music Perception.

ORCID 0000-0002-9434-5100 OpenAlex
World rank
#1,068,510
of 7,710,434 ranked researchers
Rank in Japan
#14,744
of 383,136
Works
175
Citations
3.5k
Citations per work
20.0
h-index
31
i10-index 75Top 3.7% in Signal Processing
François Pachet

What does François Pachet research?

François Pachet's work is mostly in Computer Science (66%), Neuroscience (8%), Arts and Humanities (4%).

Physical Sciences: 116 works · 66.3% of their workComputer Science: 116 works · 66.3% of their workSignal Processing: 41 works · 23.3% of their workComputer Vision and Pattern Recognition: 40 works · 22.9% of their workArtificial Intelligence: 28 works · 15.9% of their workComputer Networks and Communications: 7 works · 4.2% of their workEverything else: 39 works · 22.3% of their workLife Sciences: 13 works · 7.6% of their workNeuroscience: 13 works · 7.6% of their workCognitive Neuroscience: 13 works · 7.6% of their workSocial Sciences: 7 works · 3.8% of their workArts and Humanities: 7 works · 3.8% of their workMusic: 7 works · 3.8% of their workTHEIR WORKFrançois Pachet175works
Life Sciences8%Physical Sciences66%Social Sciences4%

Their six largest subfields, inside their fields and domains; the grey slice is everything else they publish. The interactive view splits every one of their works down to single topics.

The fields and subfields, with their numbers
    1. Computer Science11666.3%
  2. Everything else3922.3%
    1. Neuroscience137.6%
    1. Arts and Humanities73.8%
  1. 1Signal Processing23% of their works
  2. 2Computer Vision and Pattern Recognition23% of their works
  3. 3Artificial Intelligence16% of their works
  4. 4Cognitive Neuroscience8% of their works
  5. 5Computer Networks and Communications4% of their works
  6. 6Music4% of their works

Research topics

Which keywords describe François Pachet's research?

The keywords of their largest research topics: Deep Learning, Interactive Evolutionary Computation, Music Generation, Audio Signal Classification, Music Information Retrieval, Auditory Cortex, Temporal Processing and Audio-Visual Speech Recognition.

Size is their works in the topics tagged with each word, from their 8 largest topics. Each links to the topic it comes from most. The words come from the keyword list OpenAlex gives each topic, not from the text of the papers, so a word can appear that none of the papers uses.

All 17 words, with their numbers
  1. Deep Learning1102 topics
  2. Interactive Evolutionary Computation931 topic
  3. Music Generation931 topic
  4. Audio Signal Classification901 topic
  5. Music Information Retrieval901 topic
  6. Auditory Cortex291 topic
  7. Temporal Processing291 topic
  8. Audio-Visual Speech Recognition201 topic
  9. Speech Enhancement201 topic
  10. Constraint Optimization131 topic
  11. Distributed Algorithms131 topic
  12. Compression121 topic
  13. Ontology121 topic
  14. Semantic Web121 topic
  15. Suffix Arrays121 topic
  16. Content-Based Retrieval101 topic
  17. Video Summarization101 topic

Where does François Pachet work?

François Pachet's main affiliation in the publication record is Sony Computer Science Laboratories, Japan.

How many publications and citations does François Pachet have?

OpenAlex counts 175 works and 3,495 citations for François Pachet, an h-index of 31, ranking #1,068,510 of 7,710,434 researchers worldwide on the quality score.

Ranked on field-normalised citation excellence (50%), output (30%) and citations (20%). Counts come from OpenAlex author records, which occasionally merge different people who share a name or split one person into several.

Papers, co-authors, who cited this work and researchers on the nearest topics have tabs of their own, above. Is this your page? Claim it with your ORCID iD, or request a correction or removal.

Discussion

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