Search results for "Pattern recognition"

showing 10 items of 2301 documents

Mathematical modeling of a vehicle crash test based on elasto-plastic unloading scenarios of spring-mass models

2011

Published version of an article in the journal: The International Journal of Advanced Manufacturing Technology. Also available from the publisher on SpringerLink: htp://dx.doi.org/10.1007/s00170-010-3056-x This paper investigates the usability of spring which exhibit nonlinear force-deflection characteristic in the area of mathematical modeling of vehicle crash. We present a method which allows us to obtain parameters of the spring-mass model basing on the full-scale experimental data analysis. Since vehicle collision is a dynamic event, it involves such phenomena as rebound and energy dissipation. Three different spring unloading scenarios (elastic, plastic, and elasto-plastic) are covered…

VDP::Mathematics and natural science: 400::Mathematics: 410::Applied mathematics: 413EngineeringTotal crash energyVehicle crashKinematicsIndustrial and Manufacturing EngineeringCoefficient of restitution; Spring-mass model; Total crash energy; Unloading stiffness; Vehicle crash; Control and Systems Engineering; Software; Mechanical Engineering; Computer Science Applications1707 Computer Vision and Pattern Recognition; Industrial and Manufacturing EngineeringSimulationEvent (probability theory)Coefficient of restitutionbusiness.industrySpring-mass modelMechanical EngineeringVDP::Technology: 500::Mechanical engineering: 570UsabilityComputer Science Applications1707 Computer Vision and Pattern RecognitionStructural engineeringDissipationCollisionComputer Science ApplicationsNonlinear systemUnloading stiffnessSpring (device)Control and Systems EngineeringCoefficient of restitutionbusinessSoftware
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A novel active contour model for unsupervised low-key image segmentation

2013

Published version of an article in the journal: Central European Journal of Engineering. Also available from the publisher at: http://dx.doi.org/10.2478/s13531-012-0050-0 Unsupervised image segmentation is greatly useful in many vision-based applications. In this paper, we aim at the unsupervised low-key image segmentation. In low-key images, dark tone dominates the background, and gray level distribution of the foreground is heterogeneous. They widely exist in the areas of space exploration, machine vision, medical imaging, etc. In our algorithm, a novel active contour model with the probability density function of gamma distribution is proposed. The flexible gamma distribution gives a bet…

VDP::Mathematics and natural science: 400::Mathematics: 410::Applied mathematics: 413Environmental EngineeringComputer scienceMachine visionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONAerospace EngineeringInitializationScale-space segmentationProbability density functionGamma distributionGeneral Materials ScienceComputer visionactive contour modelElectrical and Electronic Engineeringimage segmentationCivil and Structural EngineeringActive contour modellow-key imageSegmentation-based object categorizationbusiness.industryMechanical EngineeringVDP::Technology: 500::Mechanical engineering: 570Pattern recognitionImage segmentationEngineering (General). Civil engineering (General)Computer Science::Computer Vision and Pattern RecognitionArtificial intelligenceTA1-2040businessOpen Engineering
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Investigation of vehicle crash modeling techniques: theory and application

2013

Published version of an article in the journal: The International Journal of Advanced Manufacturing Technology. Also available from the publisher at: http://dx.doi.org/10.1007/s00170-013-5320-3 Creating a mathematical model of a vehicle crash is a task which involves considerations and analysis of different areas which need to be addressed because of the mathematical complexity of a crash event representation. Therefore, to simplify the analysis and enhance the modeling process, in this work, a brief overview of different vehicle crash modeling methodologies is proposed. The acceleration of a colliding vehicle is measured in its center of gravity—this crash pulse contains detailed informati…

VDP::Mathematics and natural science: 400::Mathematics: 410::Applied mathematics: 413Feedforward neural network; Lumped parameter models; Multiresolution analysis; Vehicle crash modeling; Control and Systems Engineering; Software; Mechanical Engineering; Computer Science Applications1707 Computer Vision and Pattern Recognition; Industrial and Manufacturing EngineeringEvent (computing)Computer scienceReliability (computer networking)Mechanical Engineeringvehicle crash modelingVDP::Technology: 500::Mechanical engineering: 570lumped parameter modelsCrashControl engineeringComputer Science Applications1707 Computer Vision and Pattern RecognitionCollisionIndustrial and Manufacturing EngineeringComputer Science Applicationsmultiresolution analysisAutoregressive modelControl and Systems Engineeringfeedforward neural networkRepresentation (mathematics)SimulationSoftwareMotor vehicle crash
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Multi-class pairwise linear dimensionality reduction using heteroscedastic schemes

2010

Accepted version of an article published in the journal: Pattern Recognition. Published version on Sciverse: http://dx.doi.org/10.1016/j.patcog.2010.01.018 Linear dimensionality reduction (LDR) techniques have been increasingly important in pattern recognition (PR) due to the fact that they permit a relatively simple mapping of the problem onto a lower-dimensional subspace, leading to simple and computationally efficient classification strategies. Although the field has been well developed for the two-class problem, the corresponding issues encountered when dealing with multiple classes are far from trivial. In this paper, we argue that, as opposed to the traditional LDR multi-class schemes…

VDP::Mathematics and natural science: 400::Mathematics: 410::Applied mathematics: 413business.industryVDP::Mathematics and natural science: 400::Information and communication science: 420::Algorithms and computability theory: 422Dimensionality reductionDecision treePattern recognitionBayes classifierLinear discriminant analysisLinear subspaceWeightingArtificial IntelligenceSignal ProcessingPairwise comparisonComputer Vision and Pattern RecognitionArtificial intelligencebusinessAlgorithmSoftwareSubspace topologyMathematics
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Mixed l-/l1 fault detection observer design for positive switched systems with time-varying delay via delta operator approach

2014

Published version of an article in the journal: International Journal of Control, Automation and Systems. Also available from the publisher at: http://dx.doi.org/10.1007/s12555-013-0466-1 This paper investigates the problem of fault detection observer design for positive switched systems with time-varying delay via delta operator approach. A new fault sensitivity measure, called l-index, is proposed. The l- fault detection observer design and multi-objective l -/l1 fault detection observer design problems are addressed. Based on the average dwell time approach and the piecewise copositive type Lyapunov-Krasovskii functional method in delta domain, sufficient conditions for the existence of …

VDP::Technology: 500::Mechanical engineering: 570Computer Science Applications1707 Computer Vision and Pattern RecognitionDelta operatorMechatronicsfault sensitivityFault (power engineering)positive switched systemsMeasure (mathematics)VDP::Mathematics and natural science: 400::Mathematics: 410::Analysis: 411Fault detection and isolationfault detectionComputer Science Applicationsdelta operatorDwell timeControl theoryControl and Systems EngineeringPiecewiseAverage dwell time; delta operator; fault detection; fault sensitivity; positive switched systems; Control and Systems Engineering; Computer Science Applications1707 Computer Vision and Pattern RecognitionSensitivity (control systems)Average dwell timeMathematics
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Spectral adaptation of hyperspectral flight lines using VHR contextual information

2014

Abstract: Due to technological constraints, hyperspectral earth observation imagery are often a mosaic of overlapping flight lines collected in different passes over the area of interest. This causes variations in aqcuisition conditions such that the reflected spectrum can vary significantly between these flight lines. Partly, this problem is solved by atmospherical correction, but residual spectral differences often remain. A probabilistic domain adaptation framework based on graph matching using Hidden Markov Random Fields was recently proposed for transforming hyperspectral data from one image to better correspond to the other. This paper investigates the use of scale and angle invariant…

VHR imageryHyperspectral imaginggraph matchingComputer sciencebusiness.industrydomain adaptationPhysicsHyperspectral imagingPattern recognitionFilter (signal processing)Rendering (computer graphics)Computer Science::Computer Vision and Pattern RecognitionFull spectral imagingtextural featuresComputer visionArtificial intelligenceHidden Markov random fieldHidden Markov modelbusiness
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Road Functional Classification Using Pattern Recognition Techniques

2019

The existing international standards suggest a methodology to assign a specific functional class to a road, by the values of some features, both geometrical and use-related. Sometimes, these characteristics are in contrast with each other and direct the analyst towards conflicting classes for a road or, worse, one or more of these features vary heterogeneously along the road. In these conditions, the analyst assigns the class that, by his capability and experience, he retains the most appropriate, in a very subjective way. On the contrary, the definition of an automatic procedure assuring an objective identification of the most appropriate functional class for each road would be desirable. …

Value (ethics)Decision support systemlcsh:TE1-450Computer science0211 other engineering and technologiesFunctional classification02 engineering and technologylcsh:TG1-470lcsh:Bridge engineeringfunctional classification; pattern recognition; road classification; road networkInfrastructure networkPattern recognition021105 building & construction0502 economics and businessSettore ICAR/04 - Strade Ferrovie Ed Aeroportilcsh:Highway engineering. Roads and pavementsRoad classificationCivil and Structural Engineering050210 logistics & transportationClass (computer programming)business.industry05 social sciencesContrast (statistics)Pattern recognitionBuilding and ConstructionFunctional classification Pattern recognition Road classification Road networkRoad networkVariable (computer science)Identification (information)Pattern recognition (psychology)Artificial intelligencebusinessThe Baltic Journal of Road and Bridge Engineering
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Feature Selection Approach based on Mutual Information and Partial Least Squares

2014

Feature selection technology can improve the modeling accuracy and reduce model’s complexity, especially for the high dimensional spectral data. Aim at this problem, feature selection approach based on mutual information (MI) and partial least square (PLS) is proposed in this paper. MI values between features and responsible variable are calculated, and the threshold value using to select final features is optimal selected based on PLS algorithm. The numbers of the latent values of the PLS and the threshold value of MI are selected according the modeling performance simultaneously. The experimental results based on the near-infrared spectrum show that the proposed approach has better perfor…

Variable (computer science)Threshold limit valuebusiness.industryPartial least squares regressionGeneral EngineeringPattern recognitionFeature selectionHigh dimensionalArtificial intelligenceMutual informationSpectral databusinessMathematicsAdvanced Materials Research
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A method for determining the position and size of optimal sequence regions for phylogenetic analysis.

1995

The availability of fast and accurate sequencing procedures along with the use of PCR has led to a proliferation of studies of variability at the molecular level in populations. Nevertheless, it is often impractical to examine long genomic stretches and a large number of individuals at the same time. In order to optimize this kind of study, we suggest a heuristic procedure for detection of the shortest region whose informational content can be considered sufficient for significant phylogenetic reconstruction. The method is based on the comparison of the pairwise genetic distances obtained from a set of sequences of reference to those obtained for different windows of variable size and posit…

Variable sizeMolecular Sequence DataBiologyNeighbor-Joining methodSet (abstract data type)Position (vector)PhylogeneticsInformationGeneticsAnimalsHumansComputer SimulationMolecular BiologyEcology Evolution Behavior and SystematicsPhylogenyGeneticsSequencePhylogenetic treeOptimal sizeFoot-and-mouth disease virusbusiness.industryPattern recognitionBootstrapContent (measure theory)Pairwise comparisonArtificial intelligenceNon-random sequencebusinessSequence AnalysisJournal of molecular evolution
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Robust H∞ sliding mode control with pole placement for a fluid power electrohydraulic actuator (EHA) system

2014

Published version of an article in the journal: International Journal of Advanced Manufacturing Technology. Also available from the publisher at: http://dx.doi.org/10.1007/s00170-014-5910-8 In this paper, we exploit the sliding mode control problem for a fluid power electrohydraulic actuator (EHA) system. To characterize the nonlinearity of the friction, the EHA system is modeled as a linear system with a system uncertainty. Practically, it is assumed that the system is also subject to the load disturbance and the external noise. An integral sliding mode controller is proposed to design. The advanced techniques such as the H ∞ control and the regional pole placement are employed to derive t…

Variable structure controlEngineeringbusiness.industrypole placementMechanical EngineeringLinear systemLinear matrix inequalitysliding mode controlComputer Science Applications1707 Computer Vision and Pattern RecognitionVDP::Technology: 500::Electrotechnical disciplines: 540Sliding mode controlLinear matrix inequalities (LMIs); Pole placement; Sliding mode control; Control and Systems Engineering; Software; Mechanical Engineering; Computer Science Applications1707 Computer Vision and Pattern Recognition; Industrial and Manufacturing EngineeringVDP::Mathematics and natural science: 400::Mathematics: 410::Analysis: 411Industrial and Manufacturing EngineeringComputer Science ApplicationsNonlinear systemFluid powerControl theoryControl and Systems EngineeringFull state feedbacklinear matrix inequalities (LMIs)ActuatorbusinessSoftwareH∞ control
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