Search results for "vector [form factor]"

showing 10 items of 770 documents

A machine learning approach for user localization exploiting connectivity data

2016

The growing popularity of Location-Based Services (LBSs) has boosted research on cheaper and more pervasive localization systems, typically relying on such monitoring equipment as Wireless Sensor Networks (WSNs), which allow to re-use the same instrumentation both for monitoring and for localization without requiring lengthy off-line training. This work addresses the localization problem, exploiting knowledge acquired in sample environments, and extensible to areas not considered in advance. Localization is turned into a learning problem, solved by a statistical algorithm. Additionally, parameter tuning is fully automated thanks to its formulation as an optimization problem based only on co…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniOptimization problemSupport vector machineRange-free localizationbusiness.industryComputer science020206 networking & telecommunicationsSample (statistics)02 engineering and technologyMachine learningcomputer.software_genreSupport vector machineSoftware deploymentArtificial IntelligenceControl and Systems Engineering0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingArtificial intelligenceInstrumentation (computer programming)Electrical and Electronic EngineeringbusinessWireless sensor networkcomputerWireless sensor network
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Text localization from photos

2009

In this paper a new text extraction algorithm is proposed. In real scenes the text is usually overlapped or is part of the background. To identify the text regions, in complex conditions, a method exploiting a “multi-resolution feature based method” for extracting text with undefined dimension has been developed. Once identified, the multi-resolution information are merged and skimmed through a set of Support Vector Machines (SVM). The tests and the comparisons with other techniques, performed on heterogeneous images, have shown the effectiveness of the proposed.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionibusiness.industryComputer scienceFeature extractionPattern recognitionSupport vector machineSet (abstract data type)Text Localization Image UnderstandingDimension (vector space)Pattern recognition (psychology)Computer visionArtificial intelligencebusinessImage resolution2009 Digest of Technical Papers International Conference on Consumer Electronics
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ESSAYS ON FINANCIAL STRESS: A MIXED FREQUENCY DATA ANALYSIS

Settore SECS-P/05 - EconometriaFINANCIAL STRESS MIXED FREQUENCY DATA VECTOR AUTOREGRESSIVE (VAR) MODELS
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MAST solution of irrotational flow problems in 2D domains with strongly unstructured triangular meshes

2010

A new methodology for the solution of irrotational 2D flow problems in domains with strongly unstructured meshes is presented. A fractional time step procedure is applied to the original governing equations, solving consecutively a convective prediction system and a diffusive corrective system. The non linear components of the problem are concentrated in the prediction step, while the correction step leads to the solution of a linear system, of the order of the number of computational cells. A MArching in Space and Time (MAST) approach is applied for the solution of the convective prediction step. The major advantages of the model, as well as its ability to maintain the solution monotonicit…

Shallow water numerical models MASTConvectionNonlinear systemSpacetimeLinear systemApplied mathematicsMonotonic functionPolygon meshGeometryConservative vector fieldShallow water equationsSettore ICAR/01 - IdraulicaMathematicsAIP Conference Proceedings
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Automatic differentiation of melanoma from dysplastic nevi.

2015

International audience; Malignant melanoma causes the majority of deaths related to skin cancer. Nevertheless, it is the most treatable one, depending on its early diagnosis. The early prognosis is a challenging task for both clinicians and dermatologist, due to the characteristic similarities of melanoma with other skin lesions such as dysplastic nevi. In the past decades, several computerized lesion analysis algorithms have been proposed by the research community for detection of melanoma. These algorithms mostly focus on differentiating melanoma from benign lesions and few have considered the case of melanoma against dysplastic nevi. In this paper, we consider the most challenging task a…

Shape featuresSkin Neoplasms[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/ImagingDysplastic02 engineering and technology[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]030218 nuclear medicine & medical imagingColourPattern Recognition Automated0302 clinical medicine0202 electrical engineering electronic engineering information engineeringMelanoma[ SDV.IB.IMA ] Life Sciences [q-bio]/Bioengineering/ImagingRadiological and Ultrasound Technology[ INFO.INFO-IM ] Computer Science [cs]/Medical ImagingMelanomaClassificationComputer Graphics and Computer-Aided DesignDermoscopy imaging3. Good healthRandom forest020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionAlgorithmsmedicine.medical_specialtyAutomatic differentiationFeature extractionHealth InformaticsDermoscopySensitivity and SpecificityDiagnosis Differential03 medical and health sciencesLesion analysisMachine learningImage Interpretation Computer-Assistedmedicine[INFO.INFO-IM]Computer Science [cs]/Medical ImagingHumansRadiology Nuclear Medicine and imagingTextureneoplasmsbusiness.industry[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]medicine.diseaseDermatologySupport vector machineBag-of-words modelSkin cancerbusinessDysplastic Nevus SyndromeComputerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
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A probabilistic compressive sensing framework with applications to ultrasound signal processing

2019

Abstract The field of Compressive Sensing (CS) has provided algorithms to reconstruct signals from a much lower number of measurements than specified by the Nyquist-Shannon theorem. There are two fundamental concepts underpinning the field of CS. The first is the use of random transformations to project high-dimensional measurements onto a much lower-dimensional domain. The second is the use of sparse regression to reconstruct the original signal. This assumes that a sparse representation exists for this signal in some known domain, manifested by a dictionary. The original formulation for CS specifies the use of an l 1 penalised regression method, the Lasso. Whilst this has worked well in l…

Signal processing0209 industrial biotechnologyBayesian methodsComputer scienceTKAerospace Engineering02 engineering and technologycomputer.software_genre01 natural sciencesRelevance vector machineNDTSettore ING-IND/14 - Progettazione Meccanica E Costruzione Di Macchine020901 industrial engineering & automationLasso (statistics)0103 physical sciencesUltrasoundUncertainty quantification010301 acousticsSparse representationCivil and Structural EngineeringSignal processingSignal reconstructionMechanical EngineeringProbabilistic logicSparse approximationCompressive sensingComputer Science ApplicationsCompressed sensingControl and Systems EngineeringRelevance Vector MachineData miningcomputer
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An Automatic System for the Analysis and Classification of Human Atrial Fibrillation Patterns from Intracardiac Electrograms

2008

This paper presents an automatic system for the analysis and classification of atrial fibrillation (AF) patterns from bipolar intracardiac signals. The system is made up of: 1) a feature- extraction module that defines and extracts a set of measures potentially useful for characterizing AF types on the basis of their degree of organization; 2) a feature-selection module (based on the Jeffries-Matusita distance and a branch and bound search algorithm) identifying the best subset of features for discriminating different AF types; and 3) a support vector machine technique-based classification module that automatically discriminates the AF types according to the Wells' criteria. The automatic s…

Signal processingComputer scienceFeature extractionBiomedical EngineeringFeature extraction and selectionFeature selectionSensitivity and SpecificityIntracardiac injectionPattern Recognition AutomatedArtificial IntelligenceSearch algorithmAtrial FibrillationmedicineHumansDiagnosis Computer-AssistedIntracardiac ElectrogramArrhythmia organizationSignal processingmedicine.diagnostic_testbusiness.industrySupport vector machines (SVMs)Reproducibility of ResultsPattern recognitionAtrial fibrillationHuman atrial fibrillationmedicine.diseaseSupport vector machineSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaAutomatic classificationArtificial intelligenceIntracardiac electrogrambusinessElectrocardiographyAlgorithmsIEEE Transactions on Biomedical Engineering
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Support Vector Machines Framework for Linear Signal Processing

2005

This paper presents a support vector machines (SVM) framework to deal with linear signal processing (LSP) problems. The approach relies on three basic steps for model building: (1) identifying the suitable base of the Hilbert signal space in the model, (2) using a robust cost function, and (3) minimizing a constrained, regularized functional by means of the method of Lagrange multipliers. Recently, autoregressive moving average (ARMA) system identification and non-parametric spectral analysis have been formulated under this framework. The generalized, yet simple, formulation of SVM LSP problems is particularized here for three different issues: parametric spectral estimation, stability of I…

Signal processingTelecomunicacionesSupport vector machinesSystem identificationLinear signal processingSpectral density estimationSpectral estimationSupport vector machineGamma filterControl and Systems EngineeringControl theoryComplex ARMASignal ProcessingAutoregressive–moving-average model3325 Tecnología de las TelecomunicacionesComputer Vision and Pattern RecognitionElectrical and Electronic EngineeringInfinite impulse responseDigital filterAlgorithmSoftwareParametric statisticsMathematics
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Geometric Singular Perturbation Theory Beyond Normal Hyperbolicity

2001

Geometric Singular Perturbation theory has traditionally dealt only with perturbation problems near normally hyperbolic manifolds of singularities. In this paper we want to show how blow up techniques can permit enlarging the applicability to non-normally hyperbolic points. We will present the method on well chosen examples in the plane and in 3-space.

Singular perturbationPhase portraitSingular solutionMathematical analysisPerturbation (astronomy)Vector fieldGravitational singularityCenter manifoldMathematics
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Multiple Canard Cycles in Generalized Liénard Equations

2001

AbstractThe paper treats multiple limit cycle bifurcations in singular perturbation problems of planar vector fields. The results deal with any number of parameters. Proofs are based on the techniques introduced in “Canard Cycles and Center Manifolds” (F. Dumortier and R. Roussarie, 1996, Mem. Amer. Math. Soc., 121). The presentation is limited to generalized Liénard equations εx+α(x, c)x+β(x, c)=0.

Singular perturbationPure mathematicsApplied MathematicsLimit cycleMathematical analysisPlanar vector fieldsCenter (group theory)Mathematical proofAnalysisMathematicsJournal of Differential Equations
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