François Septier

1.2k total citations
43 papers, 691 citations indexed

About

François Septier is a scholar working on Artificial Intelligence, Computer Networks and Communications and Electrical and Electronic Engineering. According to data from OpenAlex, François Septier has authored 43 papers receiving a total of 691 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 13 papers in Computer Networks and Communications and 13 papers in Electrical and Electronic Engineering. Recurrent topics in François Septier's work include Target Tracking and Data Fusion in Sensor Networks (19 papers), Distributed Sensor Networks and Detection Algorithms (9 papers) and Gaussian Processes and Bayesian Inference (6 papers). François Septier is often cited by papers focused on Target Tracking and Data Fusion in Sensor Networks (19 papers), Distributed Sensor Networks and Detection Algorithms (9 papers) and Gaussian Processes and Bayesian Inference (6 papers). François Septier collaborates with scholars based in France, United Kingdom and Singapore. François Septier's co-authors include Avishy Carmi, Simon Godsill, Gareth W. Peters, Sze Kim Pang, Yves Delignon, Lyudmila Mihaylova, Amadou Gning, Ido Nevat, Tomoko Matsui and Laurent Clavier and has published in prestigious journals such as Automatica, IEEE Transactions on Signal Processing and Atmospheric Environment.

In The Last Decade

François Septier

40 papers receiving 677 citations

Peers

François Septier

EEE

CNC

CVPR

Yves Delignon France

Teerasit Kasetkasem Thailand

Martin Ulmke Germany

Ajith Gunatilaka Australia

Jouni Hartikainen Finland

Xiaojing Shen China

Emmanuel Duflos France

Sze Kim Pang United Kingdom

Ido Nevat Singapore

Amadou Gning United Kingdom

Yves Delignon France

François Septier

180 ×0.6

89 ×0.4

EEE

72 ×0.4

CNC

108 ×1.0

151 ×1.6

CVPR

Citations per year, relative to François Septier François Septier (= 1×) peers Yves Delignon

Countries citing papers authored by François Septier

Since Specialization

Citations

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

Fields of papers citing papers by François Septier

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of François Septier

This figure shows the co-authorship network connecting the top 25 collaborators of François Septier. A scholar is included among the top collaborators of François Septier based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with François Septier. François Septier is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Tran, Vu, François Septier, Daisuke Murakami, & Tomoko Matsui. (2024). Spatial–Temporal Temperature Forecasting Using Deep-Neural-Network-Based Domain Adaptation. Atmosphere. 15(1). 90–90. 1 indexed citations

Septier, François, et al.. (2023). Graph Regression Model for Spatial and Temporal Environmental Data—Case of Carbon Dioxide Emissions in the United States. Entropy. 25(9). 1272–1272. 1 indexed citations

Septier, François, et al.. (2022). State space partitioning based on constrained spectral clustering for block particle filtering. Signal Processing. 201. 108727–108727. 11 indexed citations

Clavier, Laurent, Gareth W. Peters, François Septier, & Ido Nevat. (2021). Impulsive noise modeling and robust receiver design. EURASIP Journal on Wireless Communications and Networking. 2021(1). 14 indexed citations

Courty, Nicolas, et al.. (2021). Subspace Detours Meet Gromov–Wasserstein. Algorithms. 14(12). 366–366. 1 indexed citations

Septier, François, et al.. (2021). Block Kalman Filter: An Asymptotic Block Particle Filter in the Linear Gaussian Case. HAL (Le Centre pour la Communication Scientifique Directe). 5574–5578. 1 indexed citations

Septier, François, et al.. (2020). A bayesian inference procedure based on inverse dispersion modelling for source term estimation in built-up environments. Atmospheric Environment. 242. 117733–117733. 12 indexed citations

Septier, François & Tomoko Matsui. (2019). A Robust High-Dimensional Bayesian Filter: THE Stochastic GH-GEnKF. 29. 614–618. 2 indexed citations

Zhang, Pengfei, Ido Nevat, Gareth W. Peters, François Septier, & Michael A. Osborne. (2018). Spatial Field Reconstruction and Sensor Selection in Heterogeneous Sensor Networks With Stochastic Energy Harvesting. IEEE Transactions on Signal Processing. 66(9). 2245–2257. 21 indexed citations

10.

Nevat, Ido, et al.. (2018). Joint Localization and Clock Offset Estimation via Time-Of-Arrival with Ranging Offset. 672–676. 3 indexed citations

11.

Myrvoll, Tor André, Jan Erik Håkegård, Tomoko Matsui, & François Septier. (2017). Counting public transport passenger using WiFi signatures of mobile devices. 1–6. 40 indexed citations

12.

Septier, François, et al.. (2015). An adaptive Bayesian inference algorithm to estimate the parameters of a hazardous atmospheric release. Atmospheric Environment. 122. 748–762. 41 indexed citations

13.

Duflos, Emmanuel, et al.. (2014). Joint estimation of state and noise parameters in a linear dynamic system with impulsive measurement noise: Application to OFDM systems. Digital Signal Processing. 35. 21–36. 5 indexed citations

14.

Septier, François, et al.. (2013). Bayesian model selection and parameter estimation in penalized regression model using SMC samplers. European Signal Processing Conference. 1–5. 3 indexed citations

15.

Septier, François & Yves Delignon. (2010). MCMC sampling for joint estimation of phase distortions and transmitted symbols in OFDM systems. Digital Signal Processing. 21(2). 341–353. 7 indexed citations

16.

Clavier, Laurent, et al.. (2010). α-stable interference modeling and cauchy receiver for an IR-UWB Ad Hoc network. IEEE Transactions on Communications. 58(6). 1748–1757. 48 indexed citations

17.

Septier, François, Avishy Carmi, & Simon Godsill. (2009). Tracking of Multiple Contaminant Clouds. Cambridge University Engineering Department Publications Database. 10 indexed citations

18.

Septier, François, Sze Kim Pang, Avishy Carmi, & Simon Godsill. (2009). On MCMC-Based particle methods for Bayesian filtering: Application to multitarget tracking. 360–363. 37 indexed citations

19.

Septier, François, et al.. (2009). Pilot‐Aided Sequential Monte Carlo Estimation of Phase Distortions and Transmitted Symbols in Multicarrier Systems. Journal of Electrical and Computer Engineering. 2010(1). 5 indexed citations

20.

Septier, François, et al.. (2008). Non-Pilot-Aided Sequential Monte Carlo Method to Joint Signal, Phase Noise, and Frequency Offset Estimation in Multicarrier Systems. EURASIP Journal on Advances in Signal Processing. 2008(1). 10 indexed citations

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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