Journals
[J8] Courbot J-B, Duval V and Legras B (2020), “Sparse analysis for mesoscale convective systems tracking”, Signal Processing: Image Communication. Vol. 85, pp. 115854. Elsevier.
[J7] Foucault L, Verrier N, Debailleul M, Courbot J-B, Colicchio B, Simon B, Vonna L, Haeberlé O (2019), “Versatile transmission/reflection tomographic diffractive microscopy approach“, J. Opt. Soc. Am. A 36, C18-C27.
[J6] Courbot J-B, Mazet V, Monfrini E, and Collet C (2019), “Pairwise Markov Fields for Segmentation in Astronomical Hyperspectral Images”, Signal Processing. Vol. 163C, pp. 41-48. Elsevier. [URL].
[J5] Courbot J-B, Monfrini E, Mazet V and Collet C (2018), “Oriented Triplet Markov Fields”, Pattern Recognition Letters. Elsevier. [URL] [Code]
[J4] Bacon R et al. (2017), “The MUSE Hubble Ultra Deep Field Survey-I. Survey description, data reduction, and source detection”, Astronomy & Astrophysics. Vol. 608, pp. A1. EDP Sciences. [URL]
[J3] Courbot J-B, Mazet V, Monfrini E and Collet C (2017), “Extended faint source detection in astronomical hyperspectral images”, Signal Processing. Vol. 135, pp. 274-283. Elsevier. [URL] [Code]
[J2] Courbot J-B, Rust E, Monfrini E and Collet C (2016), “Vertebra segmentation based on two-step refinement”, Journal of computational surgery. Vol. 4(1), pp. 1. Springer. [URL]
[J1] Wisotzki L, et al. (2016), “Extended Lyman alpha haloes around individual high-redshift galaxies revealed by MUSE”, Astronomy & Astrophysics. Vol. 587, pp. A98. EDP Sciences. [URL]
Conferences
[C14] Courbot J-B and Mazet V, “Pairwise and Hidden Markov Random Fields for Image Segmentation“, 28th European Signal Processing Conference (EUSIPCO), 2020.
[C13] Courbot J-B and Colicchio B, “Boosting the Sliding Frank-Wolfe solver for 3D deconvolution”, international Traveling Workshop on Interactions between low-complexity data models and Sensing Techniques (iTWIST), 2020.
[C12] Gangloff H, Courbot J-B, Monfrini E, Collet C, “Spatial Triplet Markov Trees for Auxiliary Variational Inference in Spatial Bayes Networks“, 6th Stochastic Modeling Techniques and Data Analysis International Conference (SMTDA), 2020.
[C11] Verrier N, Foucault L, Debailleul M, Courbot J-B, Colicchio B, Simon B, Vonna L, Haeberlé O, “Mirror-effect based tomographic diffraction microscopy”, Unconventional Optical Imaging II, 2020.
[C10] Karheily S, Moukadem A, Courbot J-B, Ould Abdeslam D, “Time-Frequency features for sEMG signals classification“, In 13th International Conference on Bio-inspired systems and signal processing (Biosignals 2020).
[C9] Gangloff H, Courbot J-B, Monfrini E, Collet C, “Segmentation non-supervisée dans les champs de Markov couples gaussiens”, In GRETSI 2019: XXVIIème colloque.
[C8] Courbot J-B, Duval V, Legras B, “Analyse parcimonieuse pour la poursuite de systèmes nuageux”, In GRETSI 2019: XXVIIème colloque.
[C7] Courbot J-B, “Multi-Bernoulli Filter Implementation in Images”, 26th European Signal Processing Conference (EUSIPCO), 2018.
[C6] Courbot J-B, Monfrini E, Mazet V, and Collet C, “Triplet Markov Trees for image segmentation”, Statistical Signal Processing (SSP), 2018 IEEE Workshop on., pp. 233-237. [URL]
[C5] Courbot J-B, Monfrini E, Mazet V and Collet C (2017), “Arbres de Markov triplets pour la segmentation d’images”, In GRETSI 2017: XXVIème colloque. [URL]
[C4] Courbot J-B, Monfrini E, Mazet V and Collet C (2016), “Oriented Triplet Markov Field for Hyperspectral Image Segmentation”, In IEEE Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing. [URL]
[C3] Courbot J-B, Mazet V, Monfrini E and Collet C (2016), “Detection of faint extended sources in hyperspectral data and application to HDF-S MUSE observations”, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016, pp. 1891-1895. [URL]
[C2] Courbot J-B, Rust E, Monfrini E and Collet C (2015), “2-Step robust vertebra segmentation”, In Image Processing Theory, Tools and Applications (IPTA), 2015 International Conference on. , pp. 157-162. [URL]
[C1] Courbot J-B, Rust E, Monfrini E and Collet C (2015), “Segmentation robuste de vertèbres”, In GRETSI 2015: XXVème colloque. [URL]
PhD thesis
Courbot J-B (2017), “Statistical hyperspectral image processing for diffuse object detection : application to the astronomical images from the MUSE spectro-imager.”. Thesis at: Université de Strasbourg., October, 2017. [URL]
Talks
♦ Détection de sources ténues dans des images hyperspectrales astronomiques, Réunion scientifique du GDR ISIS “Inversion et problèmes multi-“, march 2017.
♦ The MUSE Instrument for Lyman-alpha Haloes Detection, séminaire de l’Observatoire de Strasbourg, march 2016.
♦ MUSE : les observations astronomiques et leur traitement, Séminaire TIPIC, february 2016.
♦ Statistical Modeling For Automatic Vertebra Segmentation, 5th Annual International Conference in Computational Surgery and Dual Training (Cosine), Bethesda, MD, USA, january 2015.
♦ Segmentation vertébrale coarse-to-fine et markovienne, Séminaire MIV, october 2014.