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Analyse et fusion de donnéesIA et apprentissage statistiqueTraitement de signaux, d’images et du langage

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Approches de segmentationExtraire l’informationMéthodes d’amélioration d’imagesModéliser et optimiser l'informationOrienter le processus d’optimisation

Barbara Pascal

Chercheur.euse – Chargé / chargée de recherche

Equipe : SIMS

Employeur : Centre National de la Recherche Scientifique

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Publications déposées sur HAL

Nombre de publications retournées : 39

Revues internationales avec comité de lecture

[1] B. Pascal, N. Pustelnik, P. Abry, J. Géminard, V. Vidal. Parameter-free and fast nonlinear piecewise filtering. Application to experimental physics, in Annals of Telecommunications – annales des télécommunications, vol. 75, no. 11, pp. 655, DOI

[2] B. Pascal, S. Vaiter, N. Pustelnik, P. Abry. Automated data-driven selection of the hyperparameters for Total-Variation based texture segmentation, in Journal of Mathematical Imaging and Vision, vol. 63, pp. 923-952, DOI

[3] B. Pascal, N. Pustelnik, P. Abry. Strongly Convex Optimization for Joint Fractal Feature Estimation and Texture Segmentation, in Applied and Computational Harmonic Analysis, vol. 54, DOI

[4] B. Pascal, R. Bardenet. A covariant, discrete time-frequency representation tailored for zero-based signal detection, in IEEE Transactions on Signal Processing, vol. 70, pp. 2950-2961, DOI

[5] B. Pascal, P. Abry, N. Pustelnik, S. Roux, R. Gribonval, P. Flandrin. Nonsmooth convex optimization to estimate the Covid-19 reproduction number space-time evolution with robustness against low quality data, in IEEE Transactions on Signal Processing, vol. 70, pp. 2859-2868, DOI

[6] C. Lucas, B. Pascal, N. Pustelnik, P. Abry. Hyperparameter selection for Discrete Mumford-Shah, in Signal, Image and Video Processing, DOI

[7] G. Fort, B. Pascal, P. Abry, N. Pustelnik. Covid19 Reproduction Number: Credibility Intervals by Blockwise Proximal Monte Carlo Samplers, in IEEE Transactions on Signal Processing, vol. 71, pp. 888-900, DOI

[8] A. Moukadem, B. Pascal, J. Courbot, N. Juillet. The Analytic Stockwell Transform and its Zeros, in Chaos, Solitons & Fractals, vol. 197, pp. 116439,

[9] B. Pascal, S. Vaiter. Risk Estimate under a Time-Varying Autoregressive Model for Data-Driven Reproduction Number Estimation, in Signal Processing, pp. 110246,

[10] C. Bastidon, A. Parent, P. Abry, P. Borgnat, P. Jensen, B. Pascal. Detecting global financial crises with scarce data by multivariate nonlinear filtering, in Journal of Physics: Complexity, vol. 6, no. 3, pp. 035003, DOI

[11] P. Abry, C. Bastidon, P. Borgnat, P. Jensen, A. Parent, B. Pascal. New developments and perspectives on financial crisis indicators: How can signal processing enrich existing financial crises indicators?, in Finance Research Letters, vol. 89, pp. 109325, DOI

Conférences internationales avec comité de lecture et actes

[12] B. Pascal, N. Pustelnik, P. Abry, J. Pesquet. Block-coordinate proximal algorithms for scale-free texture segmentation, in ICASSP 2018 – IEEE International Conference on Acoustics, Speech and Signal Processing, Calgary, Canada, DOI

[13] B. Pascal, N. Pustelnik, P. Abry, M. Serres, V. Vidal. Joint estimation of local variance and local regularity for texture segmentation. Application to multiphase flow characterization., in International Conference on Image Processing (ICIP) 2018, Athens, Grèce,

[14] T. Busser, B. Pascal, N. Pustelnik, P. Abry, M. Serres, R. Philippe, V. Vidal. Ecoulement gaz-liquide dans un milieu poreux confiné : caractérisation par analyse d'images, in 22e Rencontre du Non-Linéaire, Paris, France,

[15] B. Pascal, T. Busser, N. Pustelnik, P. Abry, V. Vidal. Segmentation d'images texturées en grande dimension. Application à l'analyse d'écoulements multiphasiques, in GRETSI 2019 XXVIIème Colloque francophone de traitement du signal et des images, Lille, France,

[16] B. Pascal, V. Mauduit, N. Pustelnik, P. Abry. Scale-free Texture Segmentation: Expert Feature-based versus Deep Learning strategies, in 28th European Signal Processing Conference, Amsterdam, Pays-Bas, DOI

[17] C. Bastidon, P. Abry, P. Borgnat, P. Jensen, A. Parent, B. Pascal. Detecting global financial crises over history: A multivariate nonlinear denoising strategy, in World Economic History Conference Paris, Paris, France,

[18] H. Artigas, B. Pascal, G. Fort, P. Abry, N. Pustelnik. CREDIBILITY INTERVAL DESIGN FOR COVID19 REPRODUCTION NUMBER FROM NONSMOOTH LANGEVIN-TYPE MONTE CARLO SAMPLING, in European Signal Processing Conference (EUSIPCO), Belgrade, Serbie, DOI

[19] P. Abry, G. Fort, B. Pascal, N. Pustelnik. Estimation et intervalles de crédibilité pour le taux de reproduction de la Covid19 par échantillonnage Monte Carlo Langevin proximal, in Colloque Francophone de Traitement du Signal et des Images (GRETSI), Nancy, France,

[20] P. Abry, J. Chevallier, G. Fort, B. Pascal. Pandemic Intensity Estimation from Stochastic Approximation-based Algorithms, in 2023 IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, Herradura, Costa Rica, DOI

[21] B. Pascal, M. Lagrange. On the Robustness of Musical Timbre Perception Models: From Perceptual to Learned Approaches, in 32th European Signal Processing Conference (EUSIPCO), Lyon, France,

[22] J. Du, B. Pascal, P. Abry. Synthetic Spatiotemporal Covid19 Infection Counts to Assess Graph-Regularized Estimation of Multivariate Reproduction Numbers, in 32th European Signal Processing Conference (EUSIPCO), Lyon, France, DOI

[23] P. Abry, J. Chevallier, G. Fort, B. Pascal. Hierarchical Bayesian Estimation of COVID-19 Reproduction Number, in 2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, Hyderabad (IN), Inde,

[24] B. Pascal, H. Biermé. Detectability of patches in fractal textures for assessing Hölder exponent-based breast cancer risk evaluation, in IEEE Statistical Signal Processing Workshop, Edinburg, Royaume-Uni,

[25] B. Tamo Amougou, M. Pereyra, B. Pascal. Self-supervised conformal prediction for uncertainty quantification in Poisson imaging problems, in IEEE Statistical Signal Processing Workshop, Edinburg, Scotland, Royaume-Uni,

[26] A. Dauny, H. Han, A. Mukhamedjanova, A. Faubert, B. Pascal, D. Mateus, S. Wang. In vivo OCT angiography of mouse ovary, in SPIE Photonics West, San Francisco, états-Unis,

[27] B. Pascal, C. Launay, H. Biermé. Estimation of the Hurst exponent of noisy or blurred fractal textures. Application to computer-aided mammogram analysis, in IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2026), Barcelone, Espagne, DOI

[28] B. Pascal, P. Abry, J. Chevallier, G. Fort. A Scaled Poisson Bayesian Model for Viral Epidemic Monitoring, in IEEE International Conference on Acoustics, Speech, and Signal Processing, Barcelone, Espagne,

[29] E. Lasalle, B. Pascal. Joint reproduction number and spatial connectivity structure estimation via graph sparsity-promoting penalized functional, in IEEE International Conference on Acoustics, Speech, and Signal Processing, Barcelona, Espagne,

[30] B. Pineau, B. Pascal, S. Bourguignon. Unfolded primal-dual algorithm estimating time-varying COVID-19 reproduction numbers, in 34th European Signal Processing Conference (EUSIPCO), Bruges, Belgique,

Conférences nationales avec comité de lecture et actes

[31] H. Le, B. Pascal, N. Pustelnik, M. Foare, P. Abry. Algorithmes proximaux rapides déroulés pour l'analyse d'images fractales homogènes par morceaux, in GRETSI, Nancy, France,

[32] B. Pascal, R. Bardenet. Une famille de représentations covariantes de signaux discrets et son application à la détection de signaux à partir de leurs zéros, in Colloque Francophone de Traitement du Signal et des Images (GRETSI), Nancy, France,

[33] J. Du, B. Pascal, P. Abry. Performances comparées d'estimateurs du coefficient de reproduction de la Covid19 à l'aide de données synthétiques réalistes, in Colloque Francophone de Traitement du Signal et des Images (GRETSI), Grenoble, France,

[34] B. Pascal, J. Flamant, R. Bardenet. Transformée de Kravchuk réalignée, implémentation efficace et illustration sur signaux élémentaires et réels, in XXXe Colloque Francophone de Traitement du Signal et des Images (GRETSI), Strasbourg, France,

[35] B. Pascal, P. Abry. Modèle bayésien hiérarchique pour l'estimation du coefficient de reproduction de la COVID-19 à partir de comptes hebdomadaires, in Colloque Francophone de Traitement du Signal et des Images (GRETSI), Strasbourg, France,

[39] T. Chasle Cauchy, M. Tailleur, B. Pascal, F. Roche, M. Lagrange. Sobolev Norms in Neural Embeddings Measure Audio Morphing Regularity,

OptiMoCSI – Optimization and Monte Carlo Sampling Intertwined

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