Nicolas Dobigeon
Présentation
Nicolas Dobigeon a reçu le Diplôme d'Ingénieur en Électronique de l'ENSEEIHT et le D.E.A. (Master Recherche) en Traitement du Signal de l'Institut National Polytechnique de Toulouse (INP Toulouse) en Juin 2004. En 2007, il a obtenu un Doctorat en Traitement du Signal de l'INP de Toulouse et, en 2012, il a reçu l'Habilitation à Diriger des Recherches (HDR) de l'INP de Toulouse. De 2007 à 2008, il a été chercheur post-doctoral associé au Département Electrical Engineering and Computer Science de l'Université du Michigan à Ann Arbor. En 2008, il a été nommé à l'Institut National Polytechnique de Toulouse (Université de Toulouse, INP-ENSEEIHT) où il est actuellement Professeur. Il mène ses activités de recherche au sein de l'équipe Signal et Communications du laboratoire IRIT (UMR CNRS 5505) et et est aussi membre associé de l'équipe-projet Apprentissage Optimisation Complexité (AOC) du LabEx CIMI. Il porte une Chaire à l'Institut Interdisciplinaire d'Intelligence Artificielle 3IA ANITI (Artificial and Natural Intelligence Toulouse Institute) et est Membre Honoraire de l'Institut Universitaire de France (IUF, Promotion Junior 2017). Ses activités de recherche concernent principalement le traitement statistique du signal et des images, avec un intérêt particulier pour les problèmes inverses bayésiens rencontrés en télédétection, imagerie médicale et microscopie. Il est actuellement Senior Area Editor pour IEEE Trans. Signal Processing (depuis 2022), responsable adjoint du Département Signaux et Images de l'IRIT (depuis 2017), et membre du groupe d'animation de l'axe stratégique "Numérique et Société" à l'Université Fédérale Toulouse Midi-Pyrénées (depuis 2020). Il est le responsable de la formation de spécialité "Intelligence Artificielle pour le Traitement de l'Information" à l'INP-ENSEEIHT (depuis 2022). Il était Éditeur Associé pour IEEE Trans. Signal Processing (2020-2022), Signal Processing (2016-2020) et Digital Signal Processing (2018-2020), membre du comité technique SPTM TC de IEEE Signal Processing Society (2018-2020), membre du Comité de Direction du GDR-ISIS (2013-2018), membre nommé puis élu au Conseil National des Universités (CNU-Section 61, 2012-2016) et élu au Conseil Scientifique de Toulouse INP (2014-2016). Il a également été en charge la formation de spécialité "Traitement du Signal et des Images" au sein du Département Electronique de l'INP-ENSEEIHT (2011-2019). Il est IEEE Senior Member et membre de European Laboratory for Learning and Intelligent Systems (ELLIS). ---- Professional Webpage: https://ndobigeon.github.io/ Google Scholar Profile: https://scholar.google.com/citations?hl=en&user=YPQFwDYAAAAJ
Publications
Publications
Révéler les empreintes du pastoralisme. Quand les nouvelles technologies redéfinissent la prospection archéologique en montagneJeudi d'ITEM, Laboratoire ITEM - Université de Pau et des Pays de l'Adour, Mar 2025, Pau, France |
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Sur les sentiers du pastoralisme.Jeudi d'ITEM, Laboratoire ITEM, Mar 2025, Pau, France |
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On-the-fly spectral unmixing for real-time hyperspectral data analysisIEEE Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), Dec 2024, Helsinki, Finland |
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A deep neural network to restore pulsar dynamic spectra corrupted by radio frequency interferenceSoftware and Cyberinfrastructure for Astronomy VIII, Jun 2024, Yokohama, France. pp.131012J, ⟨10.1117/12.3018358⟩ |
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Bayesian formulation of regularization by denoising - Model and Monte Carlo samplingIEEE International Workshop on Multimedia Signal Processing (MMSP), Oct 2024, West Lafayette, IN, United States |
Mont’Prospect2.0Journée de restitution Nouvelles frontières de l'archéologie 2024, CNRS - MITI, Jan 2024, Paris, France |
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Prospecter les montagnes autrementSéminaire de laboratoire TRACES, Laboratoire TRACES (UMR 5608) - Toulouse, Oct 2023, Toulouse, France |
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Méthode MCMC plug-and-play avec a priori génératif profondXXIXème Colloque Francophone de Traitement du Signal et des Images (GRETSI 2023), Aug 2023, Grenoble, France. pp.173--176 |
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Prospecter autrement les montagnesSéminaire transversal du laboratoire TRACES (2023), Laboratoire TRACES (UMR 5608) : Travaux et Recherches Archéologiques sur les Cultures, les Espaces et les Sociétés, Sep 2023, Toulouse, France |
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A Bayesian estimation formulation to voxel-based lesion-symptom mapping30th European Signal Processing Conference (EUSIPCO 2022), European Association for Signal Processing (EURASIP), Aug 2022, Belgrade, Serbia |
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Approximation du transport optimal entre distributions empiriques par flux de normalisationXXVIIIème Colloque Francophone de Traitement du Signal et des Images (GRETSI 2022), Sep 2022, Nancy, France |
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Learning optimal transport between two empirical distributions with normalizing flowsEuropean Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2022), Sep 2022, Grenoble, France. ⟨10.48550/arXiv.2207.01246⟩ |
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Sliced-Wasserstein normalizing flows: beyond maximum likelihood training30th European Symposium on Artificial Neural Networks (ESANN 2022), Oct 2022, Bruges, Belgium. ⟨10.48550/arXiv.2207.05468⟩ |
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Informed spatial regularizations for fast fusion of astronomical imagesIEEE International Conference on Image Processing (ICIP 2022), Oct 2022, Bordeaux, France. pp.1-5 |
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Successive Nonnegative Projection Algorithm for Linear Quadratic Mixtures (EUSIPCO 2020)28th European Signal Processing Conference (EUSIPCO 2020), EURASIP : European Association for Signal Processing, Jan 2021, Amsterdam (virtual), Netherlands. pp.1951-1955, ⟨10.23919/Eusipco47968.2020.9287788⟩ |
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Successive Nonnegative Projection Algorithm for Linear Quadratic Mixtures (iTWIST 2020)International Traveling Workshop on Interactions between low-complexity data models and Sensing Techniques (iTWIST 2020), Dec 2020, Nantes (virtual), France |
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Unsupervised change detection for multimodal remote sensing images via coupled dictionary learning and sparse codingIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2020), May 2020, Barcelona, Spain. pp.4627-4631 |
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Fusion of hyperspectral and multispectral infrared astronomical images11th IEEE Workshop on Sensor Array and Multichannel Signal Processing (SAM 2020), IEEE, Jun 2020, Hangzhou, China. pp.1-5, ⟨10.1109/SAM48682.2020.9104393⟩ |
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Cofactorisation de matrices pour le démélange et la classification conjoints d'images hyperspectrales (SFPT-GH 2019)7e Colloque du groupe SFPT-GH : Groupe Hyperspectral de la Société Française de Photogrammétrie et de Télédétection (SFPT-GH 2019), Jul 2019, Toulouse, France. pp.1 |
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Matrix Cofactorization for Joint Unmixing and Classification of Hyperspectral Images27th European Signal Processing Conference (EUSIPCO 2019), Sep 2019, A Coruna, Spain. pp.1-5 |
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On variable splitting for Markov chain Monte CarloWorkshop on Signal Processing with Adaptative Sparse Structured Representations (SPARS 2019), Apr 2019, Toulouse, France. pp.1-2 |
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Reconstruction of partially sampled STEM-EELS images with atomic resolutionWorkshop on Signal Processing with Adaptative Sparse Structured Representations (SPARS 2019), Nicolas Dobigeon, Toulouse INP, France; Cédric Févotte, CNRS, France, Jul 2019, Toulouse, France |
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Reconstruction de spectres-images STEM-EELS partiellement échantillonnés16e Colloque de la Société Française des Microscopies (SFU 2019), Jul 2019, Poitiers, France. pp.74-75 |
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Un modèles augmenté asymptotiquement exact pour la restauration bayésienne d'images dégradées par un bruit de Poisson27e colloque du Groupe de Recherche et d'Etudes du Traitement du Signal et des Images (GRETSI 2019), Aug 2019, Lille, France. pp.1-4 |
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Efficient Sampling through Variable Splitting-inspired Bayesian Hierarchical ModelsICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Institute of Electrical and Electronics Engineers (IEEE), May 2019, Brighton, United Kingdom. pp.5037-5041, ⟨10.1109/ICASSP.2019.8682982⟩ |
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Bayesian Image Restoration under Poisson Noise and Log-concave PriorICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2019, Brighton, United Kingdom. pp.1712-1716, ⟨10.1109/ICASSP.2019.8683031⟩ |
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Unmixing dynamic PET images: combining spatial heterogeneity and non-Gaussian noiseIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2019), May 2019, Brighton, United Kingdom. pp.1373-1377 |
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Modèles augmentés asymptotiquement exacts27e colloque du Groupe de Recherche et d'Etudes du Traitement du Signal et des Images (GRETSI 2019), Aug 2019, Lille, France. pp.1-4 |
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Cofactorisation de matrices pour le démélange et la classification conjoints d'images hyperspectrales (GRETSI 2019)27e colloque du Groupe de Recherche et d'Etudes du Traitement du Signal et des Images (GRETSI 2019), Aug 2019, Lille, France. pp.1-4 |
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Fusion d'images multispectrales et hyperspectrales pour l'observation en astronomie infrarouge27e colloque du Groupe de Recherche et d'Etudes du Traitement du Signal et des Images (GRETSI 2019), Aug 2019, Lille, France. pp.1-4 |
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Fusion of hyperspectral and multispectral infrared astronomical images (SPARS 2019)Workshop on Signal Processing with Adaptative Sparse Structured Representations (SPARS 2019), Apr 2019, Toulouse, France. pp.0 |
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A comparative study of fusion-based change detection methods for multi-band images with different spectral and spatial resolutionsIEEE International Geoscience and Remote Sensing Symposium (IGARSS 2018), Jul 2018, Valencia, Spain. pp.5021-5024 |
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Sparse Bayesian binary logistic regression using the split-and-augmented Gibbs samplerIEEE International Workshop on Machine Learning for Signal Processing (MLSP 2018), Sep 2018, Aalborg, Denmark. pp.1-6 |
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LiDAR-driven spatial regularization for hyperspectral unmixingIEEE International Geoscience and Remote Sensing Symposium (IGARSS 2018), Jul 2018, Valencia, Spain. pp.1740-1743 |
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A Bayesian model for joint unmixing and robust classification of hyperspectral imageIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2018), Apr 2018, Calgary, Canada. pp.3399-3404 |
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Modèle bayésien hiérarchique pour le démélange et la classification robuste d’images hyperspectralesConférence Française de Photogrammétrie et Télédétection 2018, Jun 2018, Marne la Vallée, France. 3 p |
Prédiction des services écosystémiques dans les paysages agricoles par télédétection hyperspectrale6. Colloque de la Société Française de Photogrammétrie et Télédétection - Groupe Hyperspectrale (SFPT-GH), May 2018, Montpellier, France |
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A multiple endmember mixing model to handle spectral variability9th IEEE Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS 2018), Sep 2018, Amsterdam, Netherlands. pp.1 |
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Reconstruction of partially sampled EELS images9th IEEE Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS 2018), Sep 2018, Amsterdam, Netherlands. ⟨10.1109/WHISPERS.2018.8747104⟩ |
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Détection de changements par fusion robuste d'images multi-bandes de résolutions spatiale et spectrale différentes26eme Colloque GRETSI sur le Traitement du Signal et des Images (GRETSI 2017), Sep 2017, Juan-les-Pins, France. pp.1-4 |
Ecosystem services assessment using hyperspectral images5. Colloque de la Société Française de Photogrammétrie et Télédétection - Groupe Hyperspectrale (SFPT-GH), May 2017, Brest, France |
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Unmixing multitemporal hyperspectral images accounting for smooth and abrupt variations25th European Signal Processing Conference (EUSIPCO 2017), Aug 2017, Kos island, Greece. pp. 1-5 |
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Une formulation bayésienne du codage antiparcimonieuxGRETSI, Sep 2017, Juan-les-Pins, France |
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Fast hyperspectral unmixing in presence of sparse multiple scattering nonlinearities42nd IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2017), Mar 2017, New Orleans, United States. pp. 3111-3115 |
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Sélection du paramètre de régularisation dans le problème l2-Potts26eme Colloque GRETSI sur le Traitement du Signal et des Images (GRETSI 2017), Sep 2017, Juan-les-Pins, France. pp.1-4 |
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Une approche distribuée asynchrone pour la factorisation en matrices non-négatives - Application au démélange hyperspectral26eme Colloque GRETSI sur le Traitement du Signal et des Images (GRETSI 2017), Sep 2017, Juan-les-Pins, France. pp.1-4 |
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Bayesian Nonparametric Subspace EstimationICASSP 2017 - IEEE International Conference on Acoustics, Speech and Signal Processing, Mar 2017, New Orleans, United States. ⟨10.1109/ICASSP.2017.7952556⟩ |
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Change detection between multi-band images using a robust fusion-based approach42nd IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2017), Mar 2017, New Orleans, United States. pp. 3346-3350 |
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Un modèle bayésien pour le démélange, la segmentation et la classification robuste d’images hyperspectrales26. Colloque GRETSI 2017, Sep 2017, Juan-Les-Pins, France |
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A generalized Swendsen-Wang algorithm for Bayesian nonparametric joint segmentation of multiple imagesIEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Mar 2017, La Nouvelle Orléans, LA, United States. pp.1882-1886, ⟨10.1109/ICASSP.2017.7952483⟩ |
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Reconstruction de spectres-images partiellement échantillonnés en microscopie EELS26eme Colloque GRETSI sur le Traitement du Signal et des Images (GRETSI 2017), Sep 2017, Juan-les-Pins, France. pp.1-4 |
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Démélange d'images TEP dynamiques26eme Colloque GRETSI sur le Traitement du Signal et des Images (GRETSI 2017), Sep 2017, Juan-les-Pins, France. pp.1-4 |
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Reconstruction of randomly and partially sampled STEM spectrum-imagesMicroscopy and Microanalysis Meeting (M&M 2017), Aug 2017, Saint-Louis, Missouri, United States. pp.170-171 |
A Bayesian model for joint unmixing, clustering and classification of hyperspectral dataSéminaire des doctorants, Apr 2017, Toulouse, France. pp. 1-28 |
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Unmixing dynamic PET images with a PALM algorithm25th European Signal Processing Conference (EUSIPCO 2017), Aug 2017, Kos island, Greece. pp. 1-5 |
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Bayesian-driven criterion to automatically select the regularization parameter in the l1-Potts model42nd IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2017), Mar 2017, New Orleans, United States. pp. 1 |
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Joint segmentation of multiple images with shared classes: a Bayesian nonparametrics approachIEEE Workshop on statistical signal processing (SSP 2016), Jun 2016, Palma de Mallorca, Spain. pp.1-5, ⟨10.1109/SSP.2016.7551735⟩ |
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Democratic prior for anti-sparse codingIEEE Workshop on statistical signal processing (SSP 2016), Jun 2016, Palma de Mallorca, Spain. pp. 1-5 |
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High-resolution Hyperspectral Image Fusion Based on Spectral Unmixing19th International Conference on Information Fusion (FUSION 2016), Jul 2016, Heidelberg, Germany. pp. 1714-1719 |
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Unmixing multitemporal hyperspectral images with variability: an online algorithmIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2016), Mar 2016, Shangai, China. pp. 3351-3355 |
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Blind model-based fusion of multi-band and panchromatic imagesIEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2016), Sep 2016, Baden-Baden, Germany. pp. 21-25 |
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FUSE: a fast multi-band image fusion algorithm6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2015), Dec 2015, Cancun, Mexico. pp. 161-164 |
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A perturbed linear mixing model accounting for spectral variability23rd European Signal and Image Processing Conference (EUSIPCO 2015), Aug 2015, Nice, France. pp. 814-818 |
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Hyperspectral unmixing accounting for spatial correlations and endmember variability7th IEEE Workshop on Hyperspectral Image and SIgnal Processing: Evolution in Remote Sensing (WHISPERS 2015), Jun 2015, Tokyo, Japan. pp. 1-4 |
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Estimation de variabilité pour le démélange non-supervisé d'images hyperspectrales25eme Colloque Groupe de Recherche et d'Etudes du Traitement du Signal et des Images (GRETSI 2015), Sep 2015, Lyon, France. pp. 1-4 |
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Bayesian fusion of multispectral and hyperspectral images with unknown sensor spectral responseIEEE International Conference on Image Processing (ICIP 2014), Oct 2014, Paris, France. pp. 698-702 |
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A Bayesian approach for the joint estimation of the multifractality parameter and integral scale based on the Whittle approximation40th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2015), Apr 2015, Brisbane, Australia. pp.3886-3890, ⟨10.1109/ICASSP.2015.7178699⟩ |
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Unmixing multitemporal hyperspectral images accounting for endmember variability23rd European Signal and Image Processing Conference (EUSIPCO 2015), Aug 2015, Nice, France. pp. 1686-1690 |
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Estimation bayésienne locale du paramètre de multifractalité à l'aide d'un algorithme de Monte Carlo Hamiltonien25eme Colloque Groupe de Recherche et d'Etudes du Traitement du Signal et des Images (GRETSI 2015), Sep 2015, Lyon, France. pp. 1-5 |
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A new Bayesian unmixing algorithm for hyperspectral images mitigating endmember variabilityICASSP 2015, 40th IEEE International Conference on Acoustics, Speech, and Signal Processing, Apr 2015, Brisbane, Australia. pp.2469-2473, ⟨10.1109/ICASSP.2015.7178415⟩ |
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Bayesian fusion of multispectral and hyperspectral images using a block coordinate descent methodIEEE Workshop on Hyperspectral Image and SIgnal Processing: Evolution in Remote Sensing (WHISPERS 2015), Jun 2015, Tokyo, Japan. pp. 1-5 |
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Nonlinear unmixing of vegetated areas: a model comparison based on simulated and real hyperspectral dataIEEE Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing - WHISPERS 2014, Jun 2014, Lausanne, Switzerland. pp. 1-4 |
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Hybrid Bayesian Variational Scheme to Handle Parameter Selection in Total Variation Signal Denoising22nd European Signal and Image Processing Conference (EUSIPCO 2014), Sep 2014, Lisbonne, Portugal. pp.1716-1720 |
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Sampling from a multivariate gaussian distribution truncated on a simplex: a reviewIEEE Workshop on Statistical Signal Processing (SSP 2014), IEEE, Jun 2014, Gold Coast, Australia. pp.113-116, ⟨10.1109/SSP.2014.6884588⟩ |
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Fusion of multispectral and hyperspectral images based on sparse representation22nd European Signal and Image Processing Conference (EUSIPCO 2014), Sep 2014, Lisbon, Portugal. pp. 1577-1581 |
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Bayesian fusion of hyperspectral and multispectral imagesIEEE International Conference on Acoustics, Speech, and Signal Processing - ICASSP 2014, May 2014, Florence, Italy. pp. 3176-3180 |
Démélange non-linéaire d'images hyperspectrales : mythe ou réalité ?3ème colloque scientifique de la SFPT-GH - 2014, May 2014, Porquerolles, France |
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Learning a fast transform with a dictionaryiTwist, Aug 2014, Namur, Belgium. pp.10-12 |
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Inverse problem formulation for regularity estimation in imagesInternational Conference on Image Processing (ICIP 2014), Oct 2014, Paris, France. pp. 6081-6085 |
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A hierarchical sparsity-smoothness Bayesian model for ℓ0 + ℓ1 + ℓ2 regularizationIEEE International Conference on Acoustics, Speech, and Signal Processing - ICASSP 2014, May 2014, Florence, Italy. pp. 1901-1905 |
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Nonlinear hyperspectral unmixing using Gaussian processesIEEE Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing - WHISPERS 2013, Jun 2013, Gainesville, United States. pp. 1-4 |
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Bayesian estimation for the multifractality parameterIEEE International Conference on Acoustics, Speech, and Signal Processing - ICASSP 2013, May 2013, Vancouver, Canada. pp. 6556-6560 |
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Robust nonnegative matrix factorization for nonlinear unmixing of hyperspectral imagesIEEE Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing - WHISPERS 2013, Jun 2013, Gainesville, United States. pp. 1-4 |
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Estimation bayésienne du paramètre de multifractalité24eme Colloque Groupe de Recherche et d'Etudes du Traitement du Signal et des Images (GRETSI 2013), Sep 2013, Brest, France. pp. 1-4 |
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A robust test for nonlinear mixture detection in hyperspectral imagesIEEE International Conference on Acoustics, Speech, and Signal Processing - ICASSP 2013, May 2013, Vancouver, Canada. pp. 2149-2153 |
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Bayesian algorithm for unsupervised unmixing of hyperspectral images using a post-nonlinear model21st European Signal and Image Processing Conference (EUSIPCO 2013), Sep 2013, Marrakech, Morocco. pp. 1-5 |
Bayesian estimation of a subspaceIEEE Annual Asilomar Conference on Signals, Systems, and Computers (ASILOMAR 2011), IEEE, Nov 2011, Pacific Grove, CA, United States. pp.629--633, ⟨10.1109/ACSSC.2011.6190078⟩ |
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Variational semi-blind sparse image reconstruction with application to MRFMSPIE-IS&T Electronic Imaging (2012), Society of Photo-Optical Instrumentation Engineers (SPIE), Jan 2012, San Francisco, CA, United States. pp.(electronic medium) |
Detecting nonlinear mixtures in hyperspectral images4th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS 2012), IEEE, Jun 2012, Shangai, China. pp.(electronic medium), ⟨10.1109/WHISPERS.2012.6874285⟩ |
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Nonlinear unmixing of hyperspectral images using Gaussian processesIEEE International Conference on Acoustics, Speech, and Signal Processing (2012), Mar 2012, Kyoto, Japan. pp.1249--1252 |
Bayesian linear unmixing for spectral mixture analysisInternational Workshop on "Chemometrics in time-resolved and imaging spectroscopy - Instrumental measurements and data analysis" @ PICS 2012, Dec 2012, Lille, France |
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Constraining Martian mineralogical compositions using hyperspectral images43rd Lunar and Planetary Science Conference, Lunar and Planetary Institute (LPI), Mar 2012, Texas, United States. pp.(electronic medium) |
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Regularized Bayesian compressed sensing in ultrasound imaging20th European Signal and Image Processing Conference (EUSIPCO 2012), European Association for Signal, Speech, and Image Processing (EURASIP), Aug 2012, Bucharest, Romania. pp.2600--2604 |
Bayesian subspace estimation using CS decompositionIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2012), Mar 2012, Kyoto, Japan. pp.2437--2440, ⟨10.1109/ICASSP.2012.6288408⟩ |
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Bayesian linear unmixing of time-evolving gene expression data using a hidden Markov model20th European Signal and Image Processing Conference (EUSIPCO 2012), European Association for Signal, Speech, and Image Processing (EURASIP), Aug 2012, Bucharest, Romania. pp.944--948 |
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Accuracy and performance of linear unmixing techniques for detecting minerals on Omega/Mars Express (WHISPERS 2011)3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), Jun 2011, Lisbonne, Portugal. pp.1-4, ⟨10.1109/WHISPERS.2011.6080858⟩ |
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Joint spectral classification and unmixing using adaptative pixel neighborhoods3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS 2011), IEEE, Jun 2011, Lisbon, Portugal. pp.(electronic medium), ⟨10.1109/WHISPERS.2011.6080897⟩ |
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Labeling skin tissues in ultrasound images using a generalized Rayleigh mixture modelInternational Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), IEEE, May 2011, Prague, Czech Republic. pp.729--732, ⟨10.1109/ICASSP.2011.5946507⟩ |
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Démélange non linéaire d'images hyperspectrales à l'aide de fonctions radiales de base et de moindres carrés orthogonaux23ème Colloque du Groupe de Recherche et d'Etudes du Traitement du Signal et des Images (GRETSI 2011), Sep 2011, Bordeaux, France. pp.521-524 |
Bilinear models for nonlinear unmixing of hyperspectral images3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS 2011), IEEE, Jun 2011, Lisbon, Portugal. pp.(electronic medium), ⟨10.1109/WHISPERS.2011.6080928⟩ |
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Variational methods for spectral unmixing of hyperspectral unmixingInternational Conference on Acoustics, Speech, and Signal Processing (ICASSP 2011), IEEE, May 2011, Prague, Czech Republic. pp.957--960, ⟨10.1109/ICASSP.2011.5946564⟩ |
Echantillonnage compressé Bayésien en imagerie ultrasonoreColloque du Groupe de Recherche et d'Etudes du Traitement du Signal et des Images (GRETSI 2011), Sep 2011, Bordeaux, France. (support électronique) |
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Bayesian compressed sensing in ultrasound imaging4th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2011), Sensor Array and Multi-channel Technical Committee of the IEEE Signal Processing Society, Dec 2011, San Juan, PR, United States. pp.101--104, ⟨10.1109/CAMSAP.2011.6135897⟩ |
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Modèle Bernoulli-Gaussien pour l'analyse génétique23ème Colloque du Groupe de Recherche et d'Etudes du Traitement du Signal et des Images (GRETSI 2011), Sep 2011, Bordeaux, France. pp.505-508 |
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Bernoulli-Gaussian model for gene expression analysisInternational Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), IEEE, May 2011, Prague, Czech Republic. pp.5996--5999, ⟨10.1109/ICASSP.2011.5947728⟩ |
Méthodes variationnelles pour le démélange d'images hyperspectralesColloque du Groupe de Recherche et d'Etudes du Traitement du Signal et des Images, Sep 2011, Bordeaux, France. (support électronique) |
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Segmentation of high frequency ultrasound images using a spatially coherent generalized Rayleigh mixture model19th European Signal and Image Processing Conference (EUSIPCO 2011), European Association for Signal Processing (EURASIP); Centre Tecnològic de Telecomunicacions de Catalunya (CTTC); Universitat Politècnica de Catalunya (UPC), Aug 2011, Barcelona, Spain. pp.664--668 |
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Myopic reconstruction and its application to MRFM dataSPIE-IS&T Electronic Imaging (2011), Society of Photo-Optical Instrumentation Engineers (SPIE), Jan 2011, San Francisco, CA US, United States. pp.1--14 |
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Investigation of a small set of hyperspectral images through non-negative source separationEuropean Planetary Science Congress (EPSC 2011) @ EPSC-DPS Joint Meeting 2011, Europlanet society, Oct 2011, Nantes, France. pp.(electronic medium) |
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Accuracy and performance of linear unmixing techniques for detecting minerals on OMEGA/MExEPSC-DPS Joint Meeting, Oct 2011, Nantes, France. pp.969 |
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Nonlinear unmixing of hyperspectral images using radial basis functions and orthogonal least squaresIEEE International Geoscience and Remote Sensing Symposium (IGARSS 2011), IEEE, Jul 2011, Vancouver, Canada. pp.1151--1154, ⟨10.1109/IGARSS.2011.6049401⟩ |
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Unmixing hyperspectral images using the generalized bilinear modelIEEE International Geoscience and Remote Sensing Symposium (IGARSS 2011), IEEE, Jul 2011, Vancouver, Canada. pp.1886--1889, ⟨10.1109/IGARSS.2011.6049492⟩ |
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Non-negative matrix factorisation in contextEuropean Geosciences Union General Assembly (EGU 2011), Apr 2011, Vienna, Austria. pp.(electronic medium) |
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Supervised nonlinear spectral unmixing using a polynomial post nonlinear model for hyperspectral imageryIEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), IEEE, May 2011, Prague, Czech Republic. pp.1009--1012, ⟨10.1109/ICASSP.2011.5946577⟩ |
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Nonlinear unmixing of hyperspectral images using a generalized bilinear modelIEEE Workshop on Statistical Signal Processing (SSP 2011), IEEE Signal Processing Society, Jun 2011, Nice, France. pp.413--416, ⟨10.1109/SSP.2011.5967718⟩ |
Bayesian segmentation of chest tumors in PET Scans using a Poisson-Gamma mixture modelIEEE Workshop on Statistical Signal Processing (2011), IEEE, Jun 2011, Nice, France. pp.809--812, ⟨10.1109/SSP.2011.5967828⟩ |
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Variational methods for spectral unmixing of hyperspectral images2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2011, Prague, Czech Republic. pp.957-960, ⟨10.1109/ICASSP.2011.5946564⟩ |
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Un modèle de mélange de lois Rayleigh généralisées pour la classification des échographies cutanées23ème Colloque du Groupe de Recherche et d'Etudes du Traitement du Signal et des Images (GRETSI 2011), Sep 2011, Bordeaux, France. pp.837-840 |
MCMC algorithms for spectral unmixingAtelier "Astrostatistique en France" 2011, Dec 2011, Grenoble, France |
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Accuracy and performance of linear unmixing techniques for detecting minerals on Omega/Mars Express ((EPSC 2011)European Planetary Science Congress 2011, Oct 2011, Nantes, France. pp.(electronic medium) |
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A polynomial post nonlinear model for hyperspectral image unmixingIEEE International Geoscience and Remote Sensing Symposium (IGARSS 2011), IEEE, Jul 2011, Vancouver, Canada. pp.1882--1885, ⟨10.1109/IGARSS.2011.6049491⟩ |
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Investigating Martian and Venusian hyperspectral datasetsAGU Fall Meeting, Dec 2010, San Francisco, United States. pp.B1518 |
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Applying new spectral unmixing technique to Martian hyperspectral dataEGU General Assembly, May 2010, Vienne, Austria. pp.12824 |
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Unmixing hyperspectral images using Markov random fields30th International Workshop on Bayesian Inference and Maximun Entropy (2010), Jul 2010, Chamonix, France. pp.303--310, ⟨10.1063/1.3573630⟩ |
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Markov random fields for joint unmixing and segmentation of hyperspectral images2nd Workshop on Hyperspectral Image and SIgnal Processing: Evolution in Remote Sensing (WHISPERS 2010), IEEE, Jun 2010, Reykjavík, Iceland. pp.1--4, ⟨10.1109/WHISPERS.2010.5594841⟩ |
Accuracy and performance of optimized Bayesian source separation for hyperspectral unmixingWhispers'10, Jun 2010, Reykjavik, Iceland. pp.24 |
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Matrix approximation techniques for unsupervised hyperspectral data analysisEGU General Assembly, May 2010, Vienne, Austria. pp.10027 |
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A partially collapsed Gibbs sampler for parameters with local constraintsIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2010), IEEE, Mar 2010, Dallas, United States. pp.3886--3889, ⟨10.1109/ICASSP.2010.5495806⟩ |
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Multi-image unsupervised spectral analysisEuropean Planetary Science Congress, Sep 2010, Rome, Italy. pp.8 |
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Unsupervised Bayesian analysis of gene expression patternsIEEE Annual Asilomar Conference on Signals, Systems, and Computers (ACSSC 2010), IEEE, Nov 2010, Pacific Grove, CA, United States. pp.364--368, ⟨10.1109/ACSSC.2010.5757536⟩ |
A reversible-jump MCMC algorithm for estimating the number of endmembers in the normal compositional model. Application to the unmixing of hyperspectral imagesIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2010), IEEE, Mar 2010, Dallas, United States. pp.1222--1225, ⟨10.1109/ICASSP.2010.5495396⟩ |
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Extraction de composants purs et démélange linéaire bayésiens en imagerie hyperspectraleXIIème colloque GRETSI sur le Traitement du Signal et des Images, Sep 2009, Dijon, France. pp.CDROM |
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Material identification on martian hyperspectral images using bayesian source separationFirst IEEE Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, Aug 2009, Grenoble, France. pp.1-4, ⟨10.1109/WHISPERS.2009.5289091⟩ |
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Analyse d'images hyperspectrales à l'aide d'un modèle de mélange de spectres aléatoires22ème Colloque du Groupe de Recherche et d'Etudes du Traitement du Signal et des Images (GRETSI 2009), Sep 2009, Dijon, France. (support électronique) |
Material identification on hyperspectral images using Bayesian source separationEuropean Planetary Science Congress (EPSC 2009), Sep 2009, Potsdam, Germany. pp.(electronic medium) |
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Unmixing hyperspectral images using a normal compositional model and MCMC methods15th IEEE Workshop on Statistical Signal Processing (SSP 2009), IEEE, Aug 2009, Cardiff, Wales, United Kingdom. pp.646--649, ⟨10.1109/SSP.2009.5278494⟩ |
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An NCM-based Bayesian algorithm for hyperspectral unmixing1st IEEE Workshop on Hyperspectral Image and SIgnal Processing: Evolution in Remote Sensing (WHISPERS 2009), IEEE, Aug 2009, Grenoble, France. pp.1--4, ⟨10.1109/WHISPERS.2009.5289102⟩ |
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Multivariate approach for evaluating the composition of Meridiani spherulesEuropean Planetary Science Congress (EPSC 2009), Sep 2009, Potsdam, Germany. pp.(electronic medium) |
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Linear unmixing of hyperspectral images using a scaled gradient method15th IEEE Workshop on Statistical Signal Processing (SSP 2009), IEEE, Aug 2009, Cardiff, Wales, United Kingdom. pp.729--732, ⟨10.1109/SSP.2009.5278458⟩ |
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Library-based linear unmixing for hyperspectral imagery via reversible jump MCMC samplingIEEE Aerospace Conference (2009), Institute of Electrical and Electronics Engineers (IEEE), Mar 2009, Big Sky, Montana, United States. pp.1--6 |
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Reconstruction bayésienne images MRFM parcimonieuses22éme Colloque du Groupe de Recherche et d'Etudes du Traitement du Signal et des Images (GRETSI 2009), Sep 2009, Dijon, France. (support électronique) |
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Bayesian sparse image reconstruction for MRFMIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2009), IEEE, Apr 2009, Taipei, ROC, Taiwan. pp.2933--2936, ⟨10.1109/ICASSP.2009.4960238⟩ |
MCMC sampling for joint segmentation of wind speed and directionIEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop (DSP/SPE 2009), IEEE, Jan 2009, Marco Island, United States. pp.250--255, ⟨10.1109/DSP.2009.4785930⟩ |
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Subspace-based Bayesian blind source separation for hyperspectral imagery3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2009), Dec 2009, Aruba, Antilles, Netherlands. pp.372-375, ⟨10.1109/CAMSAP.2009.5413255⟩ |
Sparsity constrained image reconstruction for MRFMARO Multidisciplinary University Research Initiative (MURI) Magnetic Resonance Force Microscopy (MRFM) Program Progress Review (ARO MURI MRFM 2008), Jul 2008, Cornell University, Ithaca, United States |
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Joint segmentation of wind speed and direction using a hierarchical modelWorkshop on change-point detection methods and applications (2008), Sep 2008, AgroParisTech, Paris, France |
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Bayesian Linear Unmixing of Hyperspectral Images Corrupted by Colored Gaussian Noise with Unknown Covariance MatrixIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2008), IEEE, Mar 2008, Las-Vegas, Nevada, United States. pp.3433--3436, ⟨10.1109/ICASSP.2008.4518389⟩ |
Spectral Unmixing of Hyperspectral Images using a Hierarchical Bayesian ModelIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2007), IEEE, Apr 2007, Honolulu, Hawaii, United States. pp.(electronic medium), ⟨10.1109/ICASSP.2007.367060⟩ |
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Blind unmixing of linear mixtures using a hierarchical Bayesian model. Application to spectroscopic signal analysisIEEE Workshop on Statistical Signal Processing, Aug 2007, Madison, United States. pp.CDROM, ⟨10.1109/SSP.2007.4301222⟩ |
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Séparation bayésienne de sources spectrales sous contraintes de positivité et d'additivitéXXIième Colloque GRETSI sur le Traitement du Signal et des Images, Sep 2007, Troyes, France. pp.CDROM |
Change-point Detection in Astronomical Data by using a Hierarchical Model and a Bayesian Sampling Approach13th Workshop on Statistical Signal Processing (IEEE/SP 2005), IEEE, Jul 2005, Bordeaux, France. (support électronique), ⟨10.1109/SSP.2005.1628623⟩ |
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Joint segmentation of multivariate Poissonian time series. Application to Burst and Transient Source Experiments14th European Signal and Image Processing Conference (EURASIP 2006), EURASIP, Sep 2006, Florence, Italy. pp.1-5 |
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Joint segmentation of piecewise constant autoregressive processes by using a hierarchical model and a Bayesian sampling approachIEEE International Conference on Acoustics Speech and Signal Processing (ICASSP 2006), May 2006, Toulouse, France. ⟨10.1109/ICASSP.2006.1660575⟩ |
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Performance comparison of geometric and statistical methods for endmembers extraction in hyperspectral imageryImage and Signal Processing for Remote Sensing XI (2005), Sep 2005, Bruges, Belgium. pp.335--344, ⟨10.1117/12.626563⟩ |
Segmentation Conjointe de Données AstrophysiquesColloque de l'Ecole Doctorale Informatique et Télécommunications (EDIT 2005), Apr 2005, Toulouse, France |
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Segmentation conjointe de données poissonniennes20ème Colloque du Groupe de Recherche et d'Etudes du Traitement du Signal et des Images (GRETSI 2005), Sep 2005, Louvain la Neuve, Belgique. pp.238-241 |
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Caractérisation rapide des matériaux à partir des signaux chimiques (XRF) et minéralogiques (DRX) par deep-learningRayons X et Matière, Nov 2025, Orléans (45), France |
Hyperspectral EELS Image Unmixing6th Conference in Spectral Imaging (IASIM 2016), Jul 2016, Chamonix, France. 2016, Proceedings of the 6th Conference in Spectral Imaging (IASIM 2016) |
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Un modèle Bayésien de mélange de lois Poisson-Gamma pour segmenter des images TEPReconnaissance des Formes et Intelligence Artificielle (RFIA 2012), Jan 2012, Lyon, France. Actes de la conférence RFIA 2012, 2012 |
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Analysis of a collection of planetary hyperspectral images through non-negative source separationEuropean Geosciences Union General Assembly (2011), Apr 2011, Vienna, Austria. European Geosciences Union (EGU), Poster Programme SSS2.2/EMRP15/GM10.2/PS7.0, pp.EGU2011-13174, 2011 |
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Bayesian source separationChristian Jutten; Leonardo Tomazeli Duarte; Said Moussaoui. Source Separation in Physical‐Chemical Sensing, Chapter 4, Wiley, pp.151-199, 2023, Print ISBN:9781119137221 |Online ISBN:9781119137252. ⟨10.1002/9781119137252.ch4⟩ |
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Inspecter les montagne autrementBertoncello Frédérique; Ouriachi Marie-Jeanne; Nuninger Laure; Favory François. Dynamiques des peuplements, des territoires et des paysages : Bilan et perspectives en archéologie spatiale, hommages à Jean-Luc Fiches - Settlement, territory and landscape dynamics: Assessment and prospects in spatial archaeology, tribute to Jean-Luc Fiches - Actes des 42es rencontres internationales d’archéologie et d’histoire – Nice Côte d’Azur des 12-14 octobre 2022, sous la direction de Frédérique Bertoncello, Marie-Jeanne Ouriachi, Laure Nuninger, François Favory, CEPAM – UMR 7264 - Université Côte d’Azur – CNRS, 2023, Actes des Rencontres Internationales d'Archéologie et d'Histoire et d'Antibes, 2-904110-65-8 |
Perception et apprentissage de représentationsIntelligence artificielle - Regards croisés de chercheur·es, 44, La Dépêche; CNRS, pp.12-15, 2020, Le Petit Illustré |
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Linear and nonlinear unmixing in hyperspectral imagingData Handling in Science and Technology, Resolving Spectral Mixtures with Applications from Ultrafast Time-Resolved Spectroscopy to Super-Resolution Imaging, 30 - 2016 (Chapter 6), , pp.185-224, 2016, Data Handling in Science and Technology, 978-0-444-63638-6. ⟨10.1016/B978-0-444-63638-6.00006-1⟩ |
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MCMC algorithms for supervised and unsupervised linear unmixing of hyperspectral imagesMary, David; Theys, Céline; Aime, Claude. New Concepts in Imaging: Optical and Statistical Models, 59, EDP Sciences, pp.381-401, 2013, EAS Publications Series, 978-2-7598-0958-5. ⟨10.1051/eas/1359017⟩ |
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Inspecter les montagnes autrement (Année 2023)Centre national de la recherche scientifique (CNRS). 2024 |
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Segmentation of skin lesions in 2D and 3D ultrasound images using a spatially coherent generalized Rayleigh mixture modelIRIT--2011, IRIT : Institut en Recherche Informatique de Toulouse, France. 2011 |
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Modèles bayésiens hiérarchiques pour le traitement multi-capteurTraitement du signal et de l'image [eess.SP]. Institut National Polytechnique (Toulouse), 2007. Français. ⟨NNT : 2007INPT014H⟩ |
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Inférence bayésienne dans des problèmes inverses, myopes et aveugles en traitement du signal et des imagesTraitement du signal et de l'image [eess.SP]. Institut National Polytechnique de Toulouse, 2012 |