Convolution mixture of FBF and modulated FBF and application to HRTEM images

International audienceIn this paper, we propose a mixture involving a fractional Brownian field and a modulated version of such a field for modeling High Resolution Transmission Electron Microscopy (HRTEM) textures. The mixture under consideration is defined from the convolution operator applied on spatial variables of the two fields under consideration. We present estimation methods for the parameters of the model (2 Hurst parameters and 2 spectral poles) based on Wavelet Packet (WP) spectrum. The relevance of our method is highlighted by its application to the analysis of HRTEM images with active phases of a catalyst.Dans cet article, nous proposons de modéliser certaines textures apparaissant dans les images à Haute Résolution de Microscopie Electronique en Transmission (HRMET) à l'aide d'un mélange composé d'un champ Brownien fractionnaire avec une version modulée d'un tel champ. Le mélange en question est basé sur un opérateur de convolution s'appliquant sur les variables spatiales des deux champs considérés. Nous présentons deux méthodes d'estimation des paramètres de Hurst du modèle en utilisant une approche par ondelettes. Nous présentons également une méthode pour localiser les pôles du modèle. Nous montrons la pertinence de ce modèle en l'appliquant à l'analyse des images HRMET contenant des phases actives d'un catalyseur. Abstract-In this paper, we propose a mixture involving a fractional Brownian field and a modulated version of such a field for modeling High Resolution Transmission Electron Microscopy (HRTEM) textures. The mixture under consideration is defined from the convolution operator applied on spatial variables of the two fields under consideration. We present estimation methods for the parameters of the model (2 Hurst parameters and 2 spectral poles) based on Wavelet Packet (WP) spectrum. The relevance of our method is highlighted by its application to the analysis of HRTEM images with active phases of a catalyst

Quantitative analysis of backchannels uttered by an interviewer during neuropsychological tests

International audienceThis paper examines in detail the backchannels uttered by a French professional interviewer during a neuropsychological test of verbal memories. These backchannels are short utterances such as oui, d'accord, uhm, etc. They are mainly produced here to encourage subjects to retrieve a set of words after their controlled encoding. We show that the choice of lexical items, their production rates and their associated prosodic contours are influenced by the subject performance and conditioned by the protocol

ARFBF MODEL FOR NON STATIONARY RANDOM FIELDS AND APPLICATION IN HRTEM IMAGES

International audienceThis paper presents a new model called Autoregressive Fractional Brownian Field (ARFBF) for analyzing textures which contain stationary and non-stationary components. The paper also proposes two estimation methods for the parameter of an isotropic fractional Brownian field based on Wavelet Packet (WP) spectrum: the Log-Regression on Diagonal WP spectrum (Log-RDWP) and the Log-Regression on Polar representation of WP spectrum (Log-RPWP). The Log-RPWP method provides a better estimation performance for small size images. We show the interest of ARFBF model and Log-RPWP for characterizing High-Resolution Transmission Electron Microscopy (HRTEM) images

CONNAISSANCES SEMANTIQUES ET MALADIE D'ALZHEIMER (APPORT DE LA NEUROPSYCHOLOGIE COGNITIVE (DOCTORAT : NEUROPSYCHOLOGIE))

LYON1-BU Santé (693882101) / SudocPARIS-BIUM (751062103) / SudocPARIS-BIUP (751062107) / SudocSudocFranceF

INTERET COMPARE DE TESTS COGNITIFS BREFS ET DU BILAN NEUROPSYCHOLOGIQUE POUR LE DIAGNOSTIC DE DEMENCE (ETUDE RETROSPECTIVE DANS LE CADRE DE LA CONSULTATION MEMOIRE DU CHU DE GRENOBLE)

GRENOBLE1-BU Médecine pharm. (385162101) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

LA MALADIE D'ALZHEIMER (THERAPEUTIQUES ET ROLE DU PHARMACIEN D'OFFICINE)

GRENOBLE1-BU Médecine pharm. (385162101) / SudocSudocFranceF

Organisation des connaissances sémantiques. Des modèles classiques aux modèles non abstractifs

International audienc

Non-stationary texture synthesis from random field modeling

International audienceThe paper presents a generalized non-stationary and fractional model for texture synthesis. The model is based on convolutions and modulation operations of fractional Brownian fields and its associated spectral representation contains many poles with unit norm. Synthesized textures generated from this model can exhibit several non-trivial fringes which can be visualized in natural textures such those involved in high resolution transmission electron microscopy

ARFBF morphological analysis - Application to the discrimination of catalyst active phases

International audienceThis paper addresses the characterization of spatial arrangements of fringes in catalysts imaged by High Resolution Transmission Electron Microscopy (HRTEM). It presents a statistical model-based approach for analyzing these fringes. The proposed approach involves Fractional Brownian Field (FBF) and 2-D AutoRegressive (AR) modeling, as well as morphological analysis. The originality of the approach consists in identifying the image background as an FBF, subtracting this background, modeling the residual by 2-D AR so as to capture fringe information and, finally, discriminating catalysts from fringe characterizations obtained by morphological analysis. The overall analysis is called ARFBF (Auto-Regressive Fractional Brownian Field) based morphology characterization

Evidencing representational specialisation of the anterior hippocampus and perirhinal cortex across memory and non-memory operations

International audienc