Search results for "methodologie"
showing 10 items of 2141 documents
Evaluation of the impact of different odour notes on typicality of caramel aroma by recombination studies
2013
Poster (1 page); International audience; Aroma is one of the main factors that contribute to the consumer acceptability of a food product. Gas Chromatography/Olfactometry (GC/O) followed by accurate quantitation and recombination studies are usually carried out to evaluate key aroma compounds. The aim of this study is to develop a new approach taking into account odor qualities and to evaluate their impact on the typicality of caramel aroma. First, 58 aroma compounds, previously identified by GC/O analyses, were sorted into 8 odorant categories: animal, caramel, sour, vegetal, roasted, floral, fruity and nutty according to GC/O descriptors. For each category, a blend of compounds was prepar…
Neural Networks in ECG Classification
2011
In this chapter, we review the vast field of application of artificial neural networks in cardiac pathology discrimination based on electrocardiographic signals. We discuss advantages and drawbacks of neural and adaptive systems in cardiovascular medicine and catch a glimpse of forthcoming developments in machine learning models for the real clinical environment. Some problems are identified in the learning tasks of beat detection, feature selection/extraction, and classification, and some proposals and suggestions are given to alleviate the problems of interpretability, overfitting, and adaptation. These have become important problems in recent years and will surely constitute the basis of…
GW170817: Implications for the Stochastic Gravitational-Wave Background from Compact Binary Coalescences
2018
The LIGO Scientific and Virgo Collaborations have announced the first detection of gravitational waves from the coalescence of two neutron stars. The merger rate of binary neutron stars estimated from this event suggests that distant, unresolvable binary neutron stars create a significant astrophysical stochastic gravitational-wave background. The binary neutron star background will add to the background from binary black holes, increasing the amplitude of the total astrophysical background relative to previous expectations. In the Advanced LIGO-Virgo frequency band most sensitive to stochastic backgrounds (near 25 Hz), we predict a total astrophysical background with amplitude $\Omega_{\rm…
Smart cameras on a chip: using complementary metal-oxide-semiconductor (CMOS) image sensors to create smart vision chips
2020
Abstract: In this chapter, we introduce the fundamental concept of smart cameras on a chip or smart vision chips that simultaneously integrate the same die image capture capability and highly complex image processing. Successive technology scaling has made possible the integration of specific processing elements designed at chip level, at column level or at pixel level. To illustrate this continuous evolution, we survey three different categories of vision chips, exploring first the pioneering works on artificial retinas, then describing the most significant computational chips, and finally presenting the most recent image processing chips able to perform complex algorithms at a high frame …
Visual saliency detection in colour images based on density estimation
2017
International audience; A simple and effective method for visual saliency detection in colour images is presented. The method is based on the common observation that local salient regions exhibit distinct geometric and and texture patterns from neighbouring regions. We model the colour distribution of local image patches with a Gaussian density and measure the saliency of each patch as the statistical distance from that density. Experimental results with public datasets and comparison with other state-of-the-art methods show the effectiveness of our method.
K-nearest neighbor driving active contours to delineate biological tumor volumes
2019
Abstract An algorithm for tumor delineation in positron emission tomography (PET) is presented. Segmentation is achieved by a local active contour algorithm, integrated and optimized with the k-nearest neighbor (KNN) classification method, which takes advantage of the stratified k-fold cross-validation strategy. The proposed approach is evaluated considering the delineation of cancers located in different body districts (i.e. brain, head and neck, and lung), and considering different PET radioactive tracers. Data are pre-processed in order to be expressed in terms of standardized uptake value, the most widely used PET quantification index. The algorithm uses an initial, operator selected re…
A computer-assisted experiment to study the influence of the point spread function in the image formation process
2018
[EN] We present a new open experimental setup assisted with LabView to be used to teach the concept of the point spread function (PSF). The PSF describes the response of an image-forming system to a point object. The PSF concept is of fundamental importance in optics since the output of an image-forming system can be simulated as the convolution of the PSF with the input object. In this work, a new graphical user interface has been developed to obtain a real-time measure of the PSF and the corresponding images provided by different lenses and pupils with different sizes and shapes. From a didactical point of view, the proposed method allows students to interpret the results in a visual and …
Ligand binding by native and recombinant juvenile hormone binding proteins: effect of pH and phospholipid vesicles on binding affinity
2011
Poster
Hidden Markov Random Fields and Direct Search Methods for Medical Image Segmentation
2016
The goal of image segmentation is to simplify the representation of an image to items meaningful and easier to analyze. Medical image segmentation is one of the fundamental problems in image processing field. It aims to provide a crucial decision support to physicians. There is no one way to perform the segmentation. There are several methods based on HMRF. Hidden Markov Random Fields (HMRF) constitute an elegant way to model the problem of segmentation. This modelling leads to the minimization of an energy function. In this paper we investigate direct search methods that are Nelder-Mead and Torczon methods to solve this optimization problem. The quality of segmentation is evaluated on grou…
Use of accelerometers and gyros for hip and knee angle estimation
2013
In this paper a wearable sensor system, consisting of accelerometers and gyros, has been studied to estimate hip and knee angles. The proposed algorithm, developed in order to avoid the error accumulation due to gyroscopes drift, has been tested on angle measurement of the hip and knee of a commercial device for assisted gait. The results have shown a good accuracy of the angles estimation, also in high angle rate movement