Search results for "Algorithm"
showing 10 items of 4887 documents
A reverse engineering approach to measure the deformations of a sailing yacht
2016
In this work, a multidisciplinary experience, aimed to study the permanent deformations of the hull of a regatta sailing yacht is described. In particular, a procedure to compare two different surfaces of the hull of a small sailing yacht, designed and manufactured at the University of Palermo, has been developed. The first one represents the original CAD model while the second one has been obtained by means of a reverse engineering approach. The reverse engineering process was performed through an automatic close-range photogrammetry survey, that has allowed to obtain very accurate measures of the hull, and a 3D modelling step by the well-known 3D computer graphics software Rhinoceros. The…
Rational supershapes for surface reconstruction
2007
Simple representation of complex 3D data sets is a fundamental problem in computer vision. From a quality control perspective, it is crucial to use efficient and simple techniques do define a reference model for further recognition or comparison tasks. In this paper, we focus on reverse engineering 3D data sets by recovering rational supershapes to build an implicit function to represent mechanical parts. We derive existing techniques for superquadrics recovery to the supershapes and we adapt the concepts introduced for the ratioquadrics to introduce the rational supershapes. The main advantage of rational supershapes over standard supershapes is that the radius is now expressed as a ration…
Reverse engineering expert visual observations: From fixations to the learning of spatial filters with a neural-gas algorithm
2013
Human beings can become experts in performing specific vision tasks, for example, doctors analysing medical images, or botanists studying leaves. With sufficient knowledge and experience, people can become very efficient at such tasks. When attempting to perform these tasks with a machine vision system, it would be highly beneficial to be able to replicate the process which the expert undergoes. Advances in eye-tracking technology can provide data to allow us to discover the manner in which an expert studies an image. This paper presents a first step towards utilizing these data for computer vision purposes. A growing-neural-gas algorithm is used to learn a set of Gabor filters which give h…
Guías EAU sobre incontinencia urinaria
2011
Contexto: Las primeras directrices sobre incontinencia de la European Association of Urology (EAU) se publicaron en 2001. Dichas directrices se han actualizado con regularidad en los últimos años. Objetivo: El objetivo de este artículo es ofrecer un resumen de la actualización de las directrices sobre incontinencia urinaria (IU) de la EAU realizada en 2009. Recogida de evidencias: El comité de trabajo de la EAU formó parte de la IV Consulta Internacional sobre Incontinencia (ICI) y, con permiso de la ICI, llevó a cabo la extracción de la información de relevancia. La metodología de la IV ICI consistió en una amplia revisión de la literatura por parte de expertos internacionales y en la crea…
An integrated framework for risk profiling of breast cancer patients following surgery.
2006
Objective: An integrated decision support framework is proposed for clinical oncologists making prognostic assessments of patients with operable breast cancer. The framework may be delivered over a web interface. It comprises a triangulation of prognostic modelling, visualisation of historical patient data and an explanatory facility to interpret risk group assignments using empirically derived Boolean rules expressed directly in clinical terms. Methods and materials: The prognostic inferences in the interface are validated in a multicentre longitudinal cohort study by modelling retrospective data from 917 patients recruited at Christie Hospital, Wilmslow between 1983 and 1989 and predictin…
The topology of vitronectin: A complementary feature for neuroblastoma risk classification based on computer‐aided detection
2019
Tumors are complex networks of constantly interacting elements: tumor cells, stromal cells, immune and stem cells, blood/lympathic vessels, nerve fibers and extracellular matrix components. These elements can influence their microenvironment through mechanical and physical signals to promote tumor cell growth. To get a better understanding of tumor biology, cooperation between multidisciplinary fields is needed. Diverse mathematic computations and algorithms have been designed to find prognostic targets and enhance diagnostic assessment. In this work, we use computational digital tools to study the topology of vitronectin, a glycoprotein of the extracellular matrix. Vitronectin is linked to…
The Stroke Riskometer (TM) App: Validation of a data collection tool and stroke risk predictor
2014
Background The greatest potential to reduce the burden of stroke is by primary prevention of first-ever stroke, which constitutes three quarters of all stroke. In addition to population-wide prevention strategies (the ‘mass’ approach), the ‘high risk’ approach aims to identify individuals at risk of stroke and to modify their risk factors, and risk, accordingly. Current methods of assessing and modifying stroke risk are difficult to access and implement by the general population, amongst whom most future strokes will arise. To help reduce the burden of stroke on individuals and the population a new app, the Stroke Riskometer™, has been developed. We aim to explore the validity of the app fo…
A Neural Architecture for Segmentation and Modelling of Range Data
2003
A novel, two stage, neural architecture for the segmentation of range data and their modeling with undeformed superquadrics is presented. The system is composed by two distinct neural stages: a SOM is used to perform data segmentation, and, for each segment, a multi-layer feed-forward network performs model estimation. The topology preserving nature of the SOM algorithm makes this architecture suited to cluster data with respect to sudden curvature variations. The second stage is designed to model and compute the inside-outside function of an undeformed superquadric in whatever attitude, starting form the (x, y, z) data triples. The network has been trained using backpropagation, and the we…
Rotation-Invariant Texture Retrieval via Signature Alignment Based on Steerable Sub-Gaussian Modeling
2008
This paper addresses the construction of a novel efficient rotation-invariant texture retrieval method that is based on the alignment in angle of signatures obtained via a steerable sub-Gaussian model. In our proposed scheme, we first construct a steerable multivariate sub-Gaussian model, where the fractional lower-order moments of a given image are associated with those of its rotated versions. The feature extraction step consists of estimating the so-called covariations between the orientation subbands of the corresponding steerable pyramid at the same or at adjacent decomposition levels and building an appropriate signature that can be rotated directly without the need of rotating the im…
Spherical nonlinear correlations for global invariant three-dimensional object recognition
2007
We define a nonlinear filtering based on correlations on unit spheres to obtain both rotation- and scale-invariant three-dimensional (3D) object detection. Tridimensionality is expressed in terms of range images. The phase Fourier transform (PhFT) of a range image provides information about the orientations of the 3D object surfaces. When the object is sequentially rotated, the amplitudes of the different PhFTs form a unit radius sphere. On the other hand, a scale change is equivalent to a multiplication of the amplitude of the PhFT by a constant factor. The effect of both rotation and scale changes for 3D objects means a change in the intensity of the unit radius sphere. We define a 3D fil…