Search results for "020201 artificial intelligence & image processing"
showing 10 items of 1827 documents
Análisis de la utilidad del algoritmo Gradient Boosting Machine (GBM) en la predicción del fracaso empresarial
2018
Este estudio, novedoso en cuanto a la utilizacion de la metodologia basada en la cultura de los algoritmos, prueba la capacidad de la tecnica ‘Gradient Boosting Machine’ (GBM) en la prediccion de l...
Sensorless control of induction motors using an extended Kalman filter and linear quadratic tracking
2017
Induction motors are the most commonly used prime-movers in industrial applications. Many induction motors supplied by frequency converters are coupled with a physical angular rotor position/velocity sensor which makes the drive complex and require maintenance. This paper presents a sensorless control structure to avoid using a physical angular rotor position/velocity sensor. The proposed method estimates and control the angular rotor velocity using optimal control theory. The optimal controller used in this paper is based on linear quadratic tracking and the states of the machine are estimated using an extended Kalman filter. Both the controller and the estimator utilize the same internal …
Multioutput Automatic Emulator for Radiative Transfer Models
2018
This paper introduces a methodology to construct emulators of costly radiative transfer models (RTMs). The proposed methodology is sequential and adaptive, and it is based on the notion of acquisition functions in Bayesian optimization. Here, instead of optimizing the unknown underlying RTM function, one aims to achieve accurate approximations. The Automatic Multi-Output Gaussian Process Emulator (AMO-GAPE) methodology combines the interpolation capabilities of Gaussian processes (GPs) with the accurate design of an acquisition function that favors sampling in low density regions and flatness of the interpolation function. We illustrate the promising capabilities of the method for the const…
Estimating Missing Information by Cluster Analysis and Normalized Convolution
2018
International audience; Smart city deals with the improvement of their citizens' quality of life. Numerous ad-hoc sensors need to be deployed to know humans' activities as well as the conditions in which these actions take place. Even if these sensors are cheaper and cheaper, their installation and maintenance cost increases rapidly with their number. We propose a methodology to limit the number of sensors to deploy by using a standard clustering technique and the normalized convolution to estimate environmental information whereas sensors are actually missing. In spite of its simplicity, our methodology lets us provide accurate assesses.
SAR Image Classification Combining Structural and Statistical Methods
2011
The main objective of this paper is to develop a new technique of SAR image classification. This technique combines structural parameters, including the Sill, the slope, the fractal dimension and the range, with statistical methods in a supervised image classification. Thanks to the range parameter, we define the suitable size of the image window used in the proposed approach of supervised image classification. This approach is based on a new way of characterising different classes identified on the image. The first step consists in determining relevant area of interest. The second step consists in characterising each area identified, by a matrix. The last step consists in automating the pr…
Modelling Complex Volume Shape Using Ellipsoid: Application to Pore Space Representation
2017
Natural shapes have complex volume forms that are usually difficult to model using simple analytical equations. The complexity of the representation is due to the heterogeneity of the physical environment and the variety of phenomena involved. In this study we consider the representation of the porous media. Thanks to the technological advances in Computed Topography scanners, the acquisition of images of complex shapes becomes possible. However, and unfortunately, the image data is not directly usable for simulation purposes. In this paper, we investigate the modeling of such shapes using a piece wise approximation of image data by ellipsoids. We propose to use a split-merge strategy and a…
Benchmark database for fine-grained image classification of benthic macroinvertebrates
2018
Managing the water quality of freshwaters is a crucial task worldwide. One of the most used methods to biomonitor water quality is to sample benthic macroinvertebrate communities, in particular to examine the presence and proportion of certain species. This paper presents a benchmark database for automatic visual classification methods to evaluate their ability for distinguishing visually similar categories of aquatic macroinvertebrate taxa. We make publicly available a new database, containing 64 types of freshwater macroinvertebrates, ranging in number of images per category from 7 to 577. The database is divided into three datasets, varying in number of categories (64, 29, and 9 categori…
What a line can say : Investigating the semiotic potential of the connecting line in data visualizations
2020
The line is a graphical element widely used in data visualizations, its purpose often being to signal a connection between other visual elements. Based on social semiotic theory, this article investigates what semiotic functions connecting lines can have and how these functions can be related to variations in form. The results show that, in addition to the basic function of connecting elements, such lines can also indicate the level of certainty, direct the viewer to read the information either as a narrative or a conceptual claim, indicate patterns of cohesion, and regulate the viewer’s position. These findings allow for further empirical research on the formation of visual conventions.
Communication cost of channel estimation interpolation for group-based vehicular communications in cellular networks
2020
Las comunicaciones inalámbricas para aplicaciones vehiculares en sistemas celulares de quinta generación (5G) deben ser de baja latencia y alta fiabilidad. Entre otros factores, la cantidad de información de control que debe intercambiarse entre cada vehículo y la estación base puede penalizar la latencia de la comunicación. Varios casos de uso vehicular 5G implican comunicaciones dentro de grupos de vehículos, por ejemplo el pelotón de vehículos. Este trabajo se centra en explotar la estructura y características de este servicio vehicular particular basado en grupos para disminuir el intercambio de información de control relacionado con la etapa de estimación del canal necesaria para las c…
Nvidia CUDA parallel processing of large FDTD meshes in a desktop computer
2020
The Finite Difference in Time Domain numerical (FDTD) method is a well know and mature technique in computational electrodynamics. Usually FDTD is used in the analysis of electromagnetic structures, and antennas. However still there is a high computational burden, which is a limitation for use in combination with optimization algorithms. The parallelization of FDTD to calculate in GPU is possible using Matlab and CUDA tools. For instance, the simulation of a planar array, with a three dimensional FDTD mesh 790x276x588, for 6200 time steps, takes one day -elapsed time- using the CPU of an Intel Core i3 at 2.4GHz in a personal computer, 8Gb RAM. This time is reduced 120 times when the calcula…