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Researcher · Institut Mines-Télécom · France

François Septier

François Septier publishes mostly in Artificial Intelligence, Electrical and Electronic Engineering and Computer Vision and Pattern Recognition, on topics such as Target Tracking and Data Fusion in Sensor Networks, Gaussian Processes and Bayesian Inference and Distributed Sensor Networks and Detection Algorithms.

ORCID 0000-0001-5931-6091 OpenAlex
World rank
#3,035,294
of 7,710,434 ranked researchers
Rank in France
#128,590
of 324,115
Works
149
Citations
1.3k
Citations per work
8.5
h-index
18
i10-index 32Top 16% in Artificial Intelligence
François Septier

What does François Septier research?

François Septier's work is mostly in Computer Science (36%), Engineering (14%), Mathematics (6%).

Physical Sciences: 91 works · 60.8% of their workComputer Science: 54 works · 36.1% of their workArtificial Intelligence: 33 works · 22.3% of their workComputer Vision and Pattern Recognition: 11 works · 7.1% of their workComputer Networks and Communications: 10 works · 6.7% of their workEngineering: 21 works · 13.8% of their workElectrical and Electronic Engineering: 21 works · 13.8% of their workMathematics: 10 works · 6.4% of their workStatistics and Probability: 10 works · 6.4% of their workEnvironmental Science: 7 works · 4.5% of their workEnvironmental Engineering: 7 works · 4.5% of their workEverything else: 58 works · 39.2% of their workTHEIR WORKFrançois Septier149works
Physical Sciences61%

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 Science5436.1%
    2. Engineering2113.8%
    3. Mathematics106.4%
    4. Environmental Science74.5%
  2. Everything else5839.2%
  1. 1Artificial Intelligence22% of their works
  2. 2Electrical and Electronic Engineering14% of their works
  3. 3Computer Vision and Pattern Recognition7% of their works
  4. 4Computer Networks and Communications7% of their works
  5. 5Statistics and Probability6% of their works
  6. 6Environmental Engineering4% of their works

Research topics

Which keywords describe François Septier's research?

The keywords of their largest research topics: Bayesian Inference, Nonlinear Estimation, Particle Filters, Variational Inference, Deep Learning, Gaussian Processes, Machine Learning and Distributed Detection.

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 19 words, with their numbers
  1. Bayesian Inference883 topics
  2. Nonlinear Estimation501 topic
  3. Particle Filters501 topic
  4. Variational Inference382 topics
  5. Deep Learning342 topics
  6. Gaussian Processes221 topic
  7. Machine Learning221 topic
  8. Distributed Detection171 topic
  9. Wireless Sensor Networks171 topic
  10. Clustering161 topic
  11. Mixture Models161 topic
  12. MIMO-OFDM151 topic
  13. Space-Time Coding151 topic
  14. Object Tracking121 topic
  15. Visual Tracking121 topic
  16. Bayesian Monte Carlo111 topic
  17. Markov Chain111 topic
  18. Power Control91 topic
  19. Wireless Networks91 topic

Where does François Septier work?

François Septier's main affiliation in the publication record is Institut Mines-Télécom, France.

How many publications and citations does François Septier have?

OpenAlex counts 149 works and 1,263 citations for François Septier, an h-index of 18, ranking #3,035,294 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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