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Researcher · Institut National de l'Audiovisuel · France

Jean-Hugues Chenot

Jean-Hugues Chenot publishes mostly in Computer Vision and Pattern Recognition, Signal Processing and Artificial Intelligence, on topics such as Image and Signal Denoising Methods, Music and Audio Processing and Sparse and Compressive Sensing Techniques.

OpenAlex
World rank
#5,152,085
of 7,710,434 ranked researchers
Rank in France
#217,569
of 324,115
Works
17
Citations
241
Citations per work
14.2
h-index
8
i10-index 5Top 60% in Computer Vision and Pattern Recognition
Jean-Hugues Chenot

What does Jean-Hugues Chenot research?

Jean-Hugues Chenot's work is mostly in Computer Science (67%), Engineering (8%), Arts and Humanities (4%).

Physical Sciences: 13 works · 75.0% of their workComputer Science: 11 works · 66.7% of their workComputer Vision and Pattern Recognition: 7 works · 43.8% of their workSignal Processing: 2 works · 10.4% of their workArtificial Intelligence: 1 works · 8.3% of their workInformation Systems: 1 works · 4.2% of their workEngineering: 1 works · 8.3% of their workComputational Mechanics: 1 works · 8.3% of their workEverything else: 4 works · 20.8% of their workSocial Sciences: 1 works · 4.2% of their workArts and Humanities: 1 works · 4.2% of their workConservation: 1 works · 4.2% of their workTHEIR WORKJean-HuguesChenot17works
Physical Sciences75%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 Science1166.7%
    2. Engineering18.3%
  2. Everything else420.8%
    1. Arts and Humanities14.2%
  1. 1Computer Vision and Pattern Recognition44% of their works
  2. 2Signal Processing10% of their works
  3. 3Artificial Intelligence8% of their works
  4. 4Computational Mechanics8% of their works
  5. 5Information Systems4% of their works
  6. 6Conservation4% of their works

Research topics

Which keywords describe Jean-Hugues Chenot's research?

The keywords of their largest research topics: Deep Learning, Convolutional Neural Networks, Neural Networks, Sparse Representation, Generative Adversarial Networks, Audio Signal Classification, Compressed Sensing and Image Denoising.

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 21 words, with their numbers
  1. Deep Learning186 topics
  2. Convolutional Neural Networks82 topics
  3. Neural Networks83 topics
  4. Sparse Representation72 topics
  5. Generative Adversarial Networks62 topics
  6. Audio Signal Classification41 topic
  7. Compressed Sensing41 topic
  8. Image Denoising41 topic
  9. Music Information Retrieval41 topic
  10. Signal Recovery41 topic
  11. Sparse Representations41 topic
  12. Image31 topic
  13. Image Inpainting31 topic
  14. Image Synthesis31 topic
  15. Super-Resolution31 topic
  16. Backpropagation Learning21 topic
  17. Computer Graphics21 topic
  18. Image Segmentation21 topic
  19. Medical Image Analysis21 topic
  20. Self-Organizing Maps21 topic
  21. Visualization21 topic

Where does Jean-Hugues Chenot work?

Jean-Hugues Chenot's main affiliation in the publication record is Institut National de l'Audiovisuel, France.

How many publications and citations does Jean-Hugues Chenot have?

OpenAlex counts 17 works and 241 citations for Jean-Hugues Chenot, an h-index of 8, ranking #5,152,085 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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