Search results for "Vector"
showing 10 items of 2660 documents
Machine learning in remote sensing data processing
2009
Remote sensing data processing deals with real-life applications with great societal values. For instance urban monitoring, fire detection or flood prediction from remotely sensed multispectral or radar images have a great impact on economical and environmental issues. To treat efficiently the acquired data and provide accurate products, remote sensing has evolved into a multidisciplinary field, where machine learning and signal processing algorithms play an important role nowadays. This paper serves as a survey of methods and applications, and reviews the latest methodological advances in machine learning for remote sensing data analysis.
High Performance FOC for Induction Motors with Low Cost ATSAM3X8E Microcontroller
2018
In this paper the Authors present the Arduino Due board application for an induction motor field oriented control (FOC) algorithm. The low cost Arduino Due board is equipped with a ATSAM3X8E microcontroller that performs the algorithm calculation, data processing, current signals and speed/position data acquisition. The control algorithm has been developed with the help of the open source Arduino integrated development environment, whereas a user friendly control interface, used to manage the speed or position set point, has been developed in Java language by means of an other open source software, namely, Processing. An experimental test bed has been set up in order to validate the FOC sys…
geomIO: An Open‐Source MATLAB Toolbox to Create the Initial Configuration of 2‐D/3‐D Thermo‐Mechanical Simulations From 2‐D Vector Drawings
2019
Creating the initial geometry and temperature configuration of 3D numerical simulations is a challenging task. Professional tools are expensive. They often have a steep learning curve and do mostly not interface with the numerical simulation software used by the geodynamics and tectonics academic community. There, we developed geomIO (geometry Input/Output), a MATLAB toolbox to create the initial configuration of geological models regarding model geometry and temperature structure. geomIO allows users to create a geo-referenced 3D volume by drawing multiple 2D cross-sections in a standard vector graphics editor. The volume is then used to assign material properties and set up initial temper…
Forest of Normalized Trees: Fast and Accurate Density Estimation of Streaming Data
2018
Density estimation of streaming data is a relevant task in numerous domains. In this paper, a novel non-parametric density estimator called FRONT (forest of normalized trees) is introduced. It uses a structure of multiple normalized trees, segments the feature space of the data stream through a periodically updated linear transformation and is able to adapt to ever evolving data streams. FRONT provides accurate density estimation and performs favorably compared to existing online density estimators in terms of the average log score on multiple standard data sets. Its low complexity, linear runtime as well as constant memory usage, makes FRONT by design suitable for large data streams. Final…
Online Density Estimation of Heterogeneous Data Streams in Higher Dimensions
2016
The joint density of a data stream is suitable for performing data mining tasks without having access to the original data. However, the methods proposed so far only target a small to medium number of variables, since their estimates rely on representing all the interdependencies between the variables of the data. High-dimensional data streams, which are becoming more and more frequent due to increasing numbers of interconnected devices, are, therefore, pushing these methods to their limits. To mitigate these limitations, we present an approach that projects the original data stream into a vector space and uses a set of representatives to provide an estimate. Due to the structure of the est…
Sequential Learning with LS-SVM for Large-Scale Data Sets
2006
We present a subspace-based variant of LS-SVMs (i.e. regularization networks) that sequentially processes the data and is hence especially suited for online learning tasks. The algorithm works by selecting from the data set a small subset of basis functions that is subsequently used to approximate the full kernel on arbitrary points. This subset is identified online from the data stream. We improve upon existing approaches (esp. the kernel recursive least squares algorithm) by proposing a new, supervised criterion for the selection of the relevant basis functions that takes into account the approximation error incurred from approximating the kernel as well as the reduction of the cost in th…
FABC: Retinal Vessel Segmentation Using AdaBoost
2010
This paper presents a method for automated vessel segmentation in retinal images. For each pixel in the field of view of the image, a 41-D feature vector is constructed, encoding information on the local intensity structure, spatial properties, and geometry at multiple scales. An AdaBoost classifier is trained on 789 914 gold standard examples of vessel and nonvessel pixels, then used for classifying previously unseen images. The algorithm was tested on the public digital retinal images for vessel extraction (DRIVE) set, frequently used in the literature and consisting of 40 manually labeled images with gold standard. Results were compared experimentally with those of eight algorithms as we…
Effective pseudopotential for energy density functionals with higher-order derivatives
2011
We derive a zero-range pseudopotential that includes all possible terms up to sixth order in derivatives. Within the Hartree-Fock approximation, it gives the average energy that corresponds to a quasi-local nuclear Energy Density Functional (EDF) built of derivatives of the one-body density matrix up to sixth order. The direct reference of the EDF to the pseudopotential acts as a constraint that divides the number of independent coupling constants of the EDF by two. This allows, e.g., for expressing the isovector part of the functional in terms of the isoscalar part, or vice versa. We also derive the analogous set of constraints for the coupling constants of the EDF that is restricted by sp…
Oscillator Strengths of Electronic Excitations with Response Theory using Phase Including Natural Orbital Functionals
2013
The key characteristics of electronic excitations of many-electron systems, the excitation energies ωα and the oscillator strengths fα, can be obtained from linear response theory. In one-electron models and within the adiabatic approximation, the zeros of the inverse response matrix, which occur at the excitation energies, can be obtained from a simple diagonalization. Particular cases are the eigenvalue equations of time-dependent density functional theory (TDDFT), time-dependent density matrix functional theory, and the recently developed phase-including natural orbital (PINO) functional theory. In this paper, an expression for the oscillator strengths fα of the electronic excitations is…
Effects of minute misregistrations of prefabricated markers for image-guided dental implant surgery: an analytical evaluation
2012
Objectives The goal of the present study was to develop a theoretical analysis of errors in implant position, which can occur owing to minute registration errors of a reference marker in a cone beam computed tomography volume when inserting an implant with a surgical stent. Material and methods A virtual dental-arch model was created using anatomic data derived from the literature. Basic trigonometry was used to compute effects of defined minute registration errors of only voxel size. The errors occurring at the implant's neck and apex both in horizontal as in vertical direction were computed for mean ±95%-confidence intervals of jaw width and length and typical implant lengths (8, 10 and 1…