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UID:6620@i2m.univ-amu.fr
DTSTART;TZID=Europe/Paris:20201127T143000
DTEND;TZID=Europe/Paris:20201127T153000
DTSTAMP:20241120T201754Z
URL:https://www.i2m.univ-amu.fr/evenements/texture-segmentation-based-on-f
 ractal-attributes-using-convex-functional-minimization-with-generalized-st
 ein-formalism-for-automated-regularization-parameter-selection/
SUMMARY:Barbara Pascal (CRIStAL (SIGMA team)\, Lille): Texture segmentation
  based on fractal attributes using convex functional minimization with gen
 eralized Stein formalism for automated regularization parameter selection
DESCRIPTION:Barbara Pascal: Texture segmentation still constitutes an ongoi
 ng challenge\, especially when processing large-size real world images. Th
 e aim of this work is twofold.\nFirst\, we provide a variational model for
  simultaneously extracting and regularizing local texture features\, su
 ch as local regularity and local variance. For this purpose\, a scale-free
  wavelet-based model\, penalized by a Total Variation regularizer\, is emb
 eddedinto a convex optimisation framework. The resulting functional is sh
 own to be strongly-convex\, leading to a fast minimization scheme.\nSecond
 \, we investigate Stein-like strategies for the selection of regularizatio
 n parameters. A generalized Stein estimator of the quadratic risk is built
 . Then it is minimized via a quasi-Newton algorithm relying on a proposed 
 generalized estimator of the gradientof the risk with respect to hyperpara
 meters\, leading to an automated and data-driven tuning of regularization 
 parameters.\nThe overall procedure is illustrated on multiphasic flow imag
 es\, analyzed as part of a long-term collaboration with physicists from th
 e Laboratoire de Physique of ENS Lyon. \n\nSlides: https://test.i2m.univ-a
 mu.fr/seminaires_signal_apprentissage/Slides/2020_11_27_B_Pascal_Marseille
 20.pdf
ATTACH;FMTTYPE=image/jpeg:https://www.i2m.univ-amu.fr/wp-content/uploads/2
 020/12/Barbara_Pascal.jpg
CATEGORIES:Séminaire,Signal et Apprentissage
LOCATION:I2M Chateau-Gombert - CMI\, Salle de Séminaire R164 (1er étage)\
 , 39 Rue Joliot Curie\, 13013 Marseille\, France\, Campus Château-Gombert
 \, 
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=39 Rue Joliot Curie\, 13013
  Marseille\, France\, Campus Château-Gombert\, ;X-APPLE-RADIUS=100;X-TITL
 E=I2M Chateau-Gombert - CMI\, Salle de Séminaire R164 (1er étage):geo:0,
 0
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