Search results for "Kernel"
showing 10 items of 357 documents
Regularization Method in Infrared Image Processing
2003
Abstract Infrared images often present distortions induced by the measurement system. Thus, image processing is a vital part of infrared measurements. A distortion model based on a convolution product is presented. Image restoration is an ill-posed problem and its solution can be obtained using regularization methods. In this paper, image restoration is performed using a variation of Tikhonov regularization that makes use of the particular form of the convolution kernel matrix, which is built as a block-circulant matrix that admits a diagonal form in the two-dimensional Fourier space. The restoration procedure is used to restore a knife-edge infrared source image.
Microbial dynamics in durum wheat kernels during aging
2020
In the present work the microbial dynamics in wheat kernels were evaluated over time. The main aim of this research was to study the resistance of lactic acid bacteria (LAB) and yeasts associated to unprocessed cereals used for bread making during long term conservation. To this purpose four Triticum durum Desf. genotypes including two modern varieties (Claudio and Simeto) and two Sicilian wheat landraces (Russello and Timilia) were analysed by a combined culture-independent and -dependent microbiological approach after one, two or three years from cultivation and threshing. DNA based MiSeq Illumina technology was applied to reveal the entire bacterial composition of all semolina samples. T…
Normal and Abnormal Tissue Classification in Positron Emission Tomography Oncological Studies
2018
Positron Emission Tomography (PET) imaging is increasingly used in radiotherapy environment as well as for staging and assessing treatment response. The ability to classify PET tissues, as normal versus abnormal tissues, is crucial for medical analysis and interpretation. For this reason, a system for classifying PET area is implemented and validated. The proposed classification is carried out using k-nearest neighbor (KNN) method with the stratified K-Fold Cross-Validation strategy to enhance the classifier reliability. A dataset of eighty oncological patients are collected for system training and validation. For every patient, lesion (abnormal tissue) and background (normal tissue around …
A DGS gesture dictionary for modelling on mobile devices
2017
ABSTRACTInteractive or Dynamic Geometry System (DGS) is a tool that help to teach and learn geometry using a computer-based interactive environment. Traditionally, the interaction with DGS is based on keyboard and mouse events where the functionalities are accessed using a menu of icons. Nevertheless, recent findings suggest that such a traditional model of interaction has a steep learning curve and is inadequate to develop DGS for devices with multi-touch screens. Thus, we propose a new interaction model for DGS based on a gesture dictionary which enables the construction and manipulation of geometric objects without the need of accessing a menu of icons. The dictionary is divided into thr…
Food predictability determines space use of endangered vultures: implications for management of supplementary feeding.
2013
Understanding space use of free-living endangered animals is key to inform management decisions for conservation planning. Like most scavengers, vultures have evolved under a context of unpredictability of food resources (i.e. exploiting scattered carcasses that are intermittently available). However, the role of predictable sources of food in shaping spatial ecology of vultures has seldom been studied in detail. Here, we quantify the home range of the Egyptian vulture (Neophron percnopterus), a long-lived raptor which has experienced severe population decline throughout its range and is qualified as endangered worldwide. To this end six adults were tracked by satellite telemetry in Spain d…
Modelling and prediction of perceptual segmentation
2017
While listening to music, we somehow make sense of a multiplicity of auditory events; for example, in popular music we are often able to recognize whether the current section is a verse or a chorus, and to identify the boundaries between these segments. This organization occurs at multiple levels, since we can discern motifs, phrases, sections and other groupings. In this work, we understand segment boundaries as instants of significant change. Several studies on music perception and cognition have strived to understand what types of changes are associated with perceptual structure. However, effects of musical training, possible differences between real-time and non real-time segmentation, and…
High-end colorimetric display characterization using an adaptive training set
2011
A new, accurate, and technology-independent display color-characterization model is introduced. It is based on polyharmonic spline interpolation and on an optimized adaptive training data set. The establishment of this model is fully automatic and requires only a few minutes, making it efficient in a practical situation. The experimental results are very good for both the forward and inverse models. Typically, the proposed model yields an average model prediction error of about 1 ∆Eab* unit or below for several displays. The maximum error is shown to be low as well. freedom given to the model considering the choice of a tar- get color space and of the kernel and smoothing factor for the int…
Spectral density estimation for stationary stable random fields
1995
International audience
Arrangements de cercles sur une sphère: Algorithmes et Applications aux modèles moléculaires representés par une union de boules
2008
Since the early work of Richard et al., geometric constructions havebeen paramount for the description of macromolecules and macro-molecularassemblies. In particular, Voronoï and related constructions have beenused to describe the packing properties of atoms, to compute molecularsurfaces, to find cavities. This thesis falls in this realm, andafter a brief introduction to protein structure, makes fourcontributions.First, using the sweep line paradigm of Bentley and Ottmann, wepresent the first effective algorithm able to construct the exactarrangement of circles on a sphere. Moreover, assuming the circlesstem from the intersection between spheres, we present a strategy to reportthe covering …
Solving chance constrained optimal control problems in aerospace via Kernel Density Estimation
2017
International audience; The goal of this paper is to show how non-parametric statistics can be used to solve some chance constrained optimization and optimal control problems. We use the Kernel Density Estimation method to approximate the probability density function of a random variable with unknown distribution , from a relatively small sample. We then show how this technique can be applied and implemented for a class of problems including the God-dard problem and the trajectory optimization of an Ariane 5-like launcher.