Zobrazeno 1 - 10
of 96
pro vyhledávání: '"Jean-François Giovannelli"'
Publikováno v:
IET Radar, Sonar & Navigation, Vol 15, Iss 8, Pp 827-840 (2021)
Abstract Here, the authors present the application of an original high resolution method, named SPRITE (for SParse Radar Imaging TEchnique), for 3D high resolution radar cross section (RCS) imaging. It is based on a regularisation scheme that account
Externí odkaz:
https://doaj.org/article/3f03fde8d82b400abd248a56e740dafe
Publikováno v:
EURASIP Journal on Advances in Signal Processing, Vol 2019, Iss 1, Pp 1-17 (2019)
Abstract The paper tackles the problem of joint deconvolution and segmentation of textured images. The images are composed of regions containing a patch of texture that belongs to a set of K possible classes. Each class is described by a Gaussian ran
Externí odkaz:
https://doaj.org/article/7d1e52bbba81462c92664b825e6af390
Autor:
Amna Klich, Catherine Mercier, Laurent Gerfault, Pierre Grangeat, Corinne Beaulieu, Elodie Degout-Charmette, Tanguy Fortin, Pierre Mahé, Jean-François Giovannelli, Jean-Philippe Charrier, Audrey Giremus, Delphine Maucort-Boulch, Pascal Roy
Publikováno v:
BMC Bioinformatics, Vol 19, Iss 1, Pp 1-12 (2018)
Abstract Background In the field of biomarker validation with mass spectrometry, controlling the technical variability is a critical issue. In selected reaction monitoring (SRM) measurements, this issue provides the opportunity of using variance comp
Externí odkaz:
https://doaj.org/article/2b146fcfe14548f3946e848d139c47b9
Publikováno v:
Atmospheric Measurement Techniques
Atmospheric Measurement Techniques, 2022, 15 (15), pp.4411-4429. ⟨10.5194/amt-15-4411-2022⟩
Atmospheric Measurement Techniques, 2022, 15 (15), pp.4411-4429. ⟨10.5194/amt-15-4411-2022⟩
Spatiotemporal statistical learning has received increased attention in the past decade, due to spatially and temporally indexed data proliferation, especially collected from satellite remote sensing. In the mean time, observational studies of clouds
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c5fb30322aca91d5c000eec8b1de4b4f
https://doi.org/10.5194/amt-15-4411-2022
https://doi.org/10.5194/amt-15-4411-2022
Publikováno v:
Adaptive Optics Systems VIII.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6d15fe1d865698a41e9462b5242bf3e2
https://doi.org/10.1117/12.2627414
https://doi.org/10.1117/12.2627414
Publikováno v:
IEEE Signal Processing Letters. 27:2069-2073
In this letter, we propose an insight into Markov Chain Monte Carlo (MCMC) algorithms and more precisely the Gibbs sampler. From a didactic toy model, based on a normal bivariate distribution, a non-asymptotic analysis is derived and estimators are f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::506a2ca2b99671d3009f3f35593f98a8
https://doi.org/10.1109/lsp.2020.3038136
https://doi.org/10.1109/lsp.2020.3038136
Publikováno v:
IEEE Transactions on Computational Imaging. 6:1059-1069
An original 3-D high resolution radar imaging approach, called SPRITE for “SParse Radar Imaging TEchnique,” is presented. It incorporates in an original way the available prior knowledge about the electromagnetic backscattering, extending the com
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::19c72cee7e1f34d4e3accba7ffcbe8b8
https://doi.org/10.1109/tci.2020.2999162
https://doi.org/10.1109/tci.2020.2999162
Publikováno v:
SSP
This paper presents a fast heuristic for comparing Bayesian models to solve inverse problems related to signal processing. We focus on problems that are convex w.r.t. the unknown signal and where no ground truth is available. The proposed heuristic i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3299ec05999cee4a0286197beac0b435
https://doi.org/10.1109/ssp49050.2021.9513766
https://doi.org/10.1109/ssp49050.2021.9513766
Publikováno v:
IEEE Transactions on Aerospace and Electronic Systems
IEEE Transactions on Aerospace and Electronic Systems, 2017, 53 (2), pp.995-1008. ⟨10.1109/TAES.2017.2667378⟩
IEEE Transactions on Aerospace and Electronic Systems, 2017, 53 (2), pp.995-1008. ⟨10.1109/TAES.2017.2667378⟩
An original 3-D radar imaging system is presented for radar cross section (RCS) analysis, i.e., to identify and characterize the radar backscattering components of an object. Based on a 3-D spherical experimental setup, where the residual echo signal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b26bd95d7e69fbc8aa0d9fe764eb065e
https://doi.org/10.1109/taes.2017.2667378
https://doi.org/10.1109/taes.2017.2667378
Autor:
Pascal Desbarats, Wen Yang, Jean-François Giovannelli, C Michelet, Zhuxin Li, N. Gordillo, Marie-Hélène Delville, Guillaume Devès, Hervé Seznec, Philippe Barberet, Sebastien Incerti
Publikováno v:
Physica Medica
Physica Medica, Elsevier, 2019, 65, pp.172-180. ⟨10.1016/j.ejmp.2019.08.022⟩
Physica Medica, Elsevier, 2019, 65, pp.172-180. ⟨10.1016/j.ejmp.2019.08.022⟩
International audience; Proton imaging can be carried out on microscopic samples by focusing the beam to a diameter ranging from a few micrometers down to a few tens of nanometers, depending on the required beam intensity and spatial resolution. Thre
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::44f5aa51fa76123bd8d54df77b768902
https://hal.archives-ouvertes.fr/hal-02281684/file/2019-109.pdf
https://hal.archives-ouvertes.fr/hal-02281684/file/2019-109.pdf
