Search results for "Machine"
showing 10 items of 2592 documents
On the beneficial effect of rotor suspension anisotropy on viscous-dry hysteretic instability
2012
The destabilizing influence of the internal friction on the supercritical rotor whirl can be efficiently counterbalanced by other external dissipative sources and/or anisotropic suspension systems. The theoretical approach may take the internal dissipation into consideration either by dry or viscous models. Nevertheless, several numerical results and a new perturbation technique of the averaging type prove that similar rotor motions and stability limits are achievable by both models, whence the linear viscous assumption appears preferable. Thus, the internal hysteretic force may be expressed by the product of an equivalent viscous coefficient and the rotor centre velocity relative to a refe…
Design and Performance of a High Temperature Superconducting Axial Flux Generator
2013
In this paper, a high temperature axial flux (HTSAF) generator is presented. In this generator the excitation of the generator is obtained by using some high temperature superconducting magnets. In order to reduce the negative effects of vibrations, the excitation is located on the stationary part of the generator. Starting, running and endurance tests of the machine are presented.
<title>Compact illuminators, collimators, and focusers with half-sperical input aperture</title>
1994
Inexpensive semi-point light sources completed with integral concentrators of the emitted radiation can find many applications in machine vision systems. Three designs of half- spherical input aperture dielectric concentrators optimized for small spot illumination, collimation, and point-focusing are discussed here. The designs provide conversion of radially emitted light into narrow beam of the desired profile by means of total internal reflection and refraction on specially shaped aspherical surfaces. Analytic expressions describing the surface shapes as well as raytracing results are presented.
Application of the image processing methods for analysis of two-phase flow in turbomachinery
2007
The aim of this research is an application of digital image analysis for working out the method, which will allow to evaluate irregularity rate of two-phase flow across various geometry of tube bundle in aspect of the shell - and - tube heat exchanger optimization. Visualization of liquid flow in the shell — side enables an analysis of flow parameters by the use of image processing and analysis methods.
Machine Learning Identification of Pro-arrhythmic Structures in Cardiac Fibrosis
2021
Cardiac fibrosis and other scarring of the heart, arising from conditions ranging from myocardial infarction to ageing, promotes dangerous arrhythmias by blocking the healthy propagation of cardiac excitation. Owing to the complexity of the dynamics of electrical signalling in the heart, however, the connection between different arrangements of blockage and various arrhythmic consequences remains poorly understood. Where a mechanism defies traditional understanding, machine learning can be invaluable for enabling accurate prediction of quantities of interest (measures of arrhythmic risk) in terms of predictor variables (such as the arrangement or pattern of obstructive scarring). In this st…
Présentation du projet ROSAS
2019
International audience
Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks
2016
This paper proposes Markovian Generative Adversarial Networks (MGANs), a method for training generative networks for efficient texture synthesis. While deep neural network approaches have recently demonstrated remarkable results in terms of synthesis quality, they still come at considerable computational costs (minutes of run-time for low-res images). Our paper addresses this efficiency issue. Instead of a numerical deconvolution in previous work, we precompute a feed-forward, strided convolutional network that captures the feature statistics of Markovian patches and is able to directly generate outputs of arbitrary dimensions. Such network can directly decode brown noise to realistic textu…
A support vector domain method for change detection in multitemporal images
2010
This paper formulates the problem of distinguishing changed from unchanged pixels in multitemporal remote sensing images as a minimum enclosing ball (MEB) problem with changed pixels as target class. The definition of the sphere-shaped decision boundary with minimal volume that embraces changed pixels is approached in the context of the support vector formalism adopting a support vector domain description (SVDD) one-class classifier. SVDD maps the data into a high dimensional feature space where the spherical support of the high dimensional distribution of changed pixels is computed. Unlike the standard SVDD, the proposed formulation of the SVDD uses both target and outlier samples for defi…
Shape Description for Content-Based Image Retrieval
2000
The present work is focused on a global image characterization based on a description of the 2D displacements of the different shapes present in the image, which can be employed for CBIR applications.To this aim, a recognition system has been developed, that detects automatically image ROIs containing single objects, and classifies them as belonging to a particular class of shapes.In our approach we make use of the eigenvalues of the covariance matrix computed from the pixel rows of a single ROI. These quantities are arranged in a vector form, and are classified using Support Vector Machines (SVMs). The selected feature allows us to recognize shapes in a robust fashion, despite rotations or…
Cluster kernels for semisupervised classification of VHR urban images
2009
In this paper, we present and apply a semisupervised support vector machine based on cluster kernels for the problem of very high resolution image classification. In the proposed setting, a base kernel working with labeled samples only is deformed by a likelihood kernel encoding similarities between unlabeled examples. The resulting kernel is used to train a standard support vector machine (SVM) classifier. Experiments carried out on very high resolution (VHR) multispectral and hyperspectral images using very few labeled examples show the relevancy of the method in the context of urban image classification. Its simplicity and the small number of parameters involved make it versatile and wor…