Combining multiple resolutions into hierarchical representations for kernel-based image classification

Geographic object-based image analysis (GEOBIA) framework has gained increasing interest recently. Following this popular paradigm, we propose a novel multiscale classification approach operating on a hierarchical image representation built from two images at different resolutions. They capture the same scene with different sensors and are naturally fused together through the hierarchical representation, where coarser levels are built from a Low Spatial Resolution (LSR) or Medium Spatial Resolution (MSR) image while finer levels are generated from a High Spatial Resolution (HSR) or Very High Spatial Resolution (VHSR) image. Such a representation allows one to benefit from the context information thanks to the coarser levels, and subregions spatial arrangement information thanks to the finer levels. Two dedicated structured kernels are then used to perform machine learning directly on the constructed hierarchical representation. This strategy overcomes the limits of conventional GEOBIA classification procedures that can handle only one or very few pre-selected scales. Experiments run on an urban classification task show that the proposed approach can highly improve the classification accuracy w.r.t. conventional approaches working on a single scale.Comment: International Conference on Geographic Object-Based Image Analysis (GEOBIA 2016), University of Twente in Enschede, The Netherland

Contours actifs pour le suivi d'objet en temps-réel : multi-topologies et multi-résolutions

Dans cet article notre objectif est de présenter des solutions au suivi d'objets multiples dans une séquence d'images avec une contrainte de temps-réel et une caméra mobile. Nous proposons une solution basée sur les modèles de contours actifs, en s'affranchissant de leurs limites biens connues liées à l'initialisation, au réglage optimal des paramètres, au coût de calcul, et à l'incapacité à gérer les changements de topologie. Pour cela, l'algorithme est basé sur des énergies originales, un processus de suivi par boîte englobante, des étapes de scission et fusion, et une analyse multirésolution des images

Segmentation par ligne de partage des eaux basée sur des connaissances texturales

La segmentation d'une image a pour but de créer des régions homogènes selon un critère défini en fonction de l'application considérée. Le critère peut être, par exemple, les valeurs des pixels de l'image ou des indices de texture. Une fois la segmentation obtenue, une classification des régions peut être effectuée afin d'associer une sémantique aux objets présents dans l'image. L'hypothèse d'homogénéité entre des pixels d'un même objet doit permettre la construction de régions correspondant aux objets de l'image. Dans le cas d'images complexes comme les images satellites à très haute résolution spatiale, l'homogénéité classique des pixels d'un même objet n'est pas valide, réduisant la qualité des segmentations obtenues. Dans cet article, nous proposons d'intégrer au processus de segmentation par ligne de partage des eaux des connaissances sous forme d'exemples étiquetés par l'utilisateur. Nous introduisons ainsi un critère d'homogénéité de plus haut niveau basé sur des connaissances texturales

Deux niveaux et deux outils d'analyse pour une meilleure segmentation de données audio

- Dans cet article, nous abordons le problème de la segmentation de données audio. Nous proposons un processus de segmentation à deux niveaux qui permet de diviser les pistes audio en courtes séquences qui sont étiquetées dans différentes classes. La segmentation est effectuée en calculant différentes caractéristiques pour chaque séquence audio. Ces caractéristiques sont calculées soit sur un segment audio complet, soit sur une trame (ensemble d'échantillons) qui est un sous-ensemble d'un segment audio. L'approche proposée pour la microsegmentation des données audio consiste en une combinaison d'un classifieur K-Means au niveau des segments et d'un système de chaînes de Markov cachées multidimensionnelles utilisant une décomposition du signal en trames. Une première classification est obtenue en utilisant le classifieur K-Means et les caractéristiques relatives aux segments. Le résultat final est alors fourni par l'utilisation des chaînes de Markov cachées multidimensionnelles et les caractéristiques relatives aux trames, en se basant sur les résultats intermédiaires fournis par la première étape. Les chaînes de Markov cachées multidimensionnelles sont une extension des chaînes de Markov cachées classiques qui permet la prise en compte de données multicomposantes. Elles sont particulièrement adaptées dans notre cas où chaque segment audio peut être représenté par plusieurs caractéristiques de différentes natures

Compositional and mechanical properties of growing cortical bone tissue: a study of the human fibula

International audienc

Spin transport properties of spinel vanadate-based heterostructures

Spin-orbit coupling and breaking of inversion symmetry are necessary ingredients to enable a pure spin current-based manipulation of the magnetization via the spin-orbit torque effect. Currently, magnetic insulator oxides with non-dissipative characteristics are being explored. When combined with non-magnetic heavy metals, known for their large spin-orbit coupling, they offer promising potential for energy-efficient spin-orbitronics applications. The intrinsic electronic correlations characterizing those strongly correlated oxides hold the promises to add extra control-knobs to the desired efficient spin-wave propagation and abrupt magnetization switching phenomena. Spinel vanadate FeV2O4 (FVO) exhibits several structural phase transitions which are accompanied by an intricate interplay of magnetic, charge and orbital orderings. When grown as a thin film onto SrTiO3, the compressive strain state induces a perpendicular magnetic anisotropy, making FVO-based heterostructures desirable for spin-orbitronics applications. In this study, we have optimised the deposition of stoichiometric and epitaxial Pt/FVO heterostructures by Pulsed Laser Deposition and examined their spin-related phenomena. From angle-dependent magnetotransport measurements, we observed both Anisotropic Magnetoresistance (AMR) and Spin Hall Magnetoresistance (SMR) effects. Our findings show the SMR component as the primary contributor to the overall magnetoresistance, whose high value of 0.12% is only comparable to properly optimized oxide-based systems

Kinetic DTI of the cervical spine: diffusivity changes in healthy subjects

Introduction The study aims to assess the influence of neck extension on water diffusivity within the cervical spinal cord. Methods IRB approved the study in 22 healthy volunteers. All subjects underwent anatomical MR and diffusion tensor imaging (DTI) at 1.5 T. The cervical cord was imaged in neutral (standard) position and extension. Segmental vertebral rotations were analyzed on sagittal T2-weighted images using the SpineView® software. Spinal cord diffusivity was measured in cross-sectional regions of interests at multiple levels (C1–C5). Results As a result of non-adapted coil geometry for spinal extension, 10 subjects had to be excluded. Image quality of the remaining 12 subjects was good without any deteriorating artifacts. Quantitative measurements of vertebral rotation angles and diffusion parameters showed good intra-rater reliability (ICC= 0.84–0.99). DTI during neck extension revealed significantly decreased fractional anisotropy (FA) and increased radial diffusivity (RD) at the C3 level and increased apparent diffusion coefficients (ADC) at the C3 and C4 levels (p < 0.01 Bonferroni corrected). The C3/C4 level corresponded to the maximal absolute change in segmental vertebral rotation between the two positions. The increase in RD correlated positively with the degree of global extension, i.e., the summed vertebral rotation angle between C1 and C5 (R= 0.77, p= 0.006). Conclusion Our preliminary results suggest that DTI can quantify changes in water diffusivity during cervical spine extension. The maximal differences in segmental vertebral rotation corresponded to the levels with significant changes in diffusivity (C3/C4). Consequently, kinetic DTI measurements may open new perspectives in the assessment of neural tissue under biomechanical constraint

Compositional and mechanical properties of growing cortical bone tissue: a study of the human fibula

International audienc

In Antisynthetase Syndrome, ACPA Are Associated With Severe and Erosive Arthritis: An Overlapping Rheumatoid Arthritis and Antisynthetase Syndrome

International audienceAbstract: Anticitrullinated peptide/protein antibodies (ACPA), which are highly specific for rheumatoid arthritis (RA), may be found in some patients with other systemic autoimmune diseases. The clinical significance of ACPA in patients with antisynthetase syndrome (ASS), a systemic disease characterized by the association of myositis, interstitial lung disease, polyarthralgia, and/or polyarthritis, has not yet been evaluated with regard to phenotype, prognosis, and response to treatment. ACPA-positive ASS patients were first identified among a French multicenter registry of patients with ASS. Additionally, all French rheumatology and internal medicine practitioners registered on the Club Rhumatismes et Inflammation web site were asked to report their observations of ASS patients with ACPA. The 17 collected patients were retrospectively studied using a standardized questionnaire and compared with 34 unselected ACPA-negative ASS patients in a case–control study. All ACPA-positive ASS patients suffered from arthritis versus 41% in the control group (P 7-year mean follow-up, extra-articular outcomes and survival were not different. ACPA-positive ASS patients showed an overlapping RA–ASS syndrome, were at high risk of refractory erosive arthritis, and might experience ASS flare when treated with antitumor necrosis factor drugs. In contrast, other biologics such as anti-CD20 mAb were effective in this context, without worsening systemic involvements

An essential role for Clp1 in assembly of polyadenylation complex CF IA and Pol II transcription termination

Polyadenylation is a co-transcriptional process that modifies mRNA 3′-ends in eukaryotes. In yeast, CF IA and CPF constitute the core 3′-end maturation complex. CF IA comprises Rna14p, Rna15p, Pcf11p and Clp1p. CF IA interacts with the C-terminal domain of RNA Pol II largest subunit via Pcf11p which links pre-mRNA 3′-end processing to transcription termination. Here, we analysed the role of Clp1p in 3′ processing. Clp1p binds ATP and interacts in CF IA with Pcf11p only. Depletion of Clp1p abolishes transcription termination. Moreover, we found that association of mutations in the ATP-binding domain and in the distant Pcf11p-binding region impair 3′-end processing. Strikingly, these mutations prevent not only Clp1p-Pcf11p interaction but also association of Pcf11p with Rna14p-Rna15p. ChIP experiments showed that Rna15p cross-linking to the 3′-end of a protein-coding gene is perturbed by these mutations whereas Pcf11p is only partially affected. Our study reveals an essential role of Clp1p in CF IA organization. We postulate that Clp1p transmits conformational changes to RNA Pol II through Pcf11p to couple transcription termination and 3′-end processing. These rearrangements likely rely on the correct orientation of ATP within Clp1p