Search results for "Image"

showing 10 items of 6818 documents

A fast and recursive algorithm for clustering large datasets with k-medians

2012

Clustering with fast algorithms large samples of high dimensional data is an important challenge in computational statistics. Borrowing ideas from MacQueen (1967) who introduced a sequential version of the $k$-means algorithm, a new class of recursive stochastic gradient algorithms designed for the $k$-medians loss criterion is proposed. By their recursive nature, these algorithms are very fast and are well adapted to deal with large samples of data that are allowed to arrive sequentially. It is proved that the stochastic gradient algorithm converges almost surely to the set of stationary points of the underlying loss criterion. A particular attention is paid to the averaged versions, which…

Statistics and ProbabilityClustering high-dimensional dataFOS: Computer and information sciencesMathematical optimizationhigh dimensional dataMachine Learning (stat.ML)02 engineering and technologyStochastic approximation01 natural sciencesStatistics - Computation010104 statistics & probabilityk-medoidsStatistics - Machine Learning[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]stochastic approximation0202 electrical engineering electronic engineering information engineeringComputational statisticsrecursive estimatorsAlmost surely[ MATH.MATH-ST ] Mathematics [math]/Statistics [math.ST]0101 mathematicsCluster analysisComputation (stat.CO)Mathematicsaveragingk-medoidsRobbins MonroApplied MathematicsEstimator[STAT.TH]Statistics [stat]/Statistics Theory [stat.TH]stochastic gradient[ STAT.TH ] Statistics [stat]/Statistics Theory [stat.TH]MedoidComputational MathematicsComputational Theory and Mathematicsonline clustering020201 artificial intelligence & image processingpartitioning around medoidsAlgorithm
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Online Principal Component Analysis in High Dimension: Which Algorithm to Choose?

2017

Summary Principal component analysis (PCA) is a method of choice for dimension reduction. In the current context of data explosion, online techniques that do not require storing all data in memory are indispensable to perform the PCA of streaming data and/or massive data. Despite the wide availability of recursive algorithms that can efficiently update the PCA when new data are observed, the literature offers little guidance on how to select a suitable algorithm for a given application. This paper reviews the main approaches to online PCA, namely, perturbation techniques, incremental methods and stochastic optimisation, and compares the most widely employed techniques in terms statistical a…

Statistics and ProbabilityComputer scienceComputationDimensionality reductionIncremental methods02 engineering and technologyMissing data01 natural sciences010104 statistics & probabilityData explosionStreaming dataPrincipal component analysis0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processing0101 mathematicsStatistics Probability and UncertaintyAlgorithmEigendecomposition of a matrixInternational Statistical Review
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Anthropometry: An R Package for Analysis of Anthropometric Data

2017

The development of powerful new 3D scanning techniques has enabled the generation of large up-to-date anthropometric databases which provide highly valued data to improve the ergonomic design of products adapted to the user population. As a consequence, Ergonomics and Anthropometry are two increasingly quantitative fields, so advanced statistical methodologies and modern software tools are required to get the maximum benefit from anthropometric data. This paper presents a new R package, called Anthropometry, which is available on the Comprehensive R Archive Network. It brings together some statistical methodologies concerning clustering, statistical shape analysis, statistical archetypal an…

Statistics and ProbabilityComputer sciencePopulationstatistical shape analysis02 engineering and technologycomputer.software_genre01 natural sciences010104 statistics & probabilitySoftware0202 electrical engineering electronic engineering information engineeringR; anthropometric data; clustering; statistical shape analysis; archetypal analysis; data depth0101 mathematicsarchetypal analysisCluster analysiseducationlcsh:Statisticslcsh:HA1-4737education.field_of_studyAnthropometric databusiness.industryStatistical shape analysisRHuman factors and ergonomicsAnthropometryanthropometric dataVignette020201 artificial intelligence & image processingData miningStatistics Probability and Uncertaintydata depthbusinesscomputerSoftwareclusteringJournal of Statistical Software
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Microstructural sensitivity of local porosity distributions

1992

The recently introduced concept of local porosity distributions for the geometric characterization of arbitrary porous media is scrutinized using computer generated pore space images. The paper presents the first direct determination of local porosity distributions from digital images. Pore space images with identical two point correlation functions are employed to analyse the geometrical sensitivity of the local porosity concept. The main finding is that local distributions can be used to discriminate between images which are indistinguishable using standard correlation functions. We also discuss the question of length scales associated with the local porosity concept.

Statistics and ProbabilityDigital imageGeometryCharacterisation of pore space in soilSensitivity (control systems)Condensed Matter PhysicsPorosityPorous mediumPhysics::GeophysicsCharacterization (materials science)MathematicsPoint correlationPhysica A: Statistical Mechanics and its Applications
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R Graphics (3rd Edition)

2020

Statistics and ProbabilityEngineeringbusiness.industryComputer graphics (images)Statistics Probability and UncertaintyGraphicsbusinesslcsh:Statisticslcsh:HA1-4737SoftwareJournal of Statistical Software
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On 1-Laplacian Elliptic Equations Modeling Magnetic Resonance Image Rician Denoising

2015

Modeling magnitude Magnetic Resonance Images (MRI) rician denoising in a Bayesian or generalized Tikhonov framework using Total Variation (TV) leads naturally to the consideration of nonlinear elliptic equations. These involve the so called $1$-Laplacian operator and special care is needed to properly formulate the problem. The rician statistics of the data are introduced through a singular equation with a reaction term defined in terms of modified first order Bessel functions. An existence theory is provided here together with other qualitative properties of the solutions. Remarkably, each positive global minimum of the associated functional is one of such solutions. Moreover, we directly …

Statistics and ProbabilityFOS: Computer and information sciencesComputer scienceNoise reductionComputer Vision and Pattern Recognition (cs.CV)Bayesian probabilityComputer Science - Computer Vision and Pattern Recognition02 engineering and technology01 natural sciencesTikhonov regularizationsymbols.namesakeMathematics - Analysis of PDEsOperator (computer programming)Rician fading0202 electrical engineering electronic engineering information engineeringFOS: MathematicsApplied mathematicsMathematics - Numerical Analysis0101 mathematicsApplied Mathematics010102 general mathematicsNumerical Analysis (math.NA)Condensed Matter PhysicsNonlinear systemModeling and Simulationsymbols020201 artificial intelligence & image processingGeometry and TopologyComputer Vision and Pattern RecognitionLaplace operatorBessel functionAnalysis of PDEs (math.AP)
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What we look at in paintings: A comparison between experienced and inexperienced art viewers

2016

How do people look at art? Are there any differences between how experienced and inexperienced art viewers look at a painting? We approach these questions by analyzing and modeling eye movement data from a cognitive art research experiment, where the eye movements of twenty test subjects, ten experienced and ten inexperienced art viewers, were recorded while they were looking at paintings. Eye movements consist of stops of the gaze as well as jumps between the stops. Hence, the observed gaze stop locations can be thought as a spatial point pattern, which can be modeled by a spatio-temporal point process. We introduce some statistical tools to analyze the spatio-temporal eye movement data, a…

Statistics and ProbabilityFOS: Computer and information sciencesCoverageComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION01 natural sciencesStatistics - Applications050105 experimental psychologyVisual arts010104 statistics & probabilitysilmänliikkeetInformationSystems_MODELSANDPRINCIPLES0501 psychology and cognitive sciencesApplications (stat.AP)0101 mathematicspoint processPaintingPoint (typography)05 social sciencesEye movementCognitioncognitive art researchtransition probabilityGazeTest (assessment)shift functionModeling and Simulationart viewersStatistics Probability and UncertaintyPsychologyintensity
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Comparative Evaluation of Community Detection Algorithms: A Topological Approach

2012

International audience; Community detection is one of the most active fields in complex networks analysis, due to its potential value in practical applications. Many works inspired by different paradigms are devoted to the development of algorithmic solutions allowing to reveal the network structure in such cohesive subgroups. Comparative studies reported in the literature usually rely on a performance measure considering the community structure as a partition (Rand Index, Normalized Mutual information, etc.). However, this type of comparison neglects the topological properties of the communities. In this article, we present a comprehensive comparative study of a representative set of commu…

Statistics and ProbabilityFOS: Computer and information sciencesPhysics - Physics and SocietyComputer science[INFO.INFO-OH]Computer Science [cs]/Other [cs.OH]Rand indexFOS: Physical sciences02 engineering and technologyPhysics and Society (physics.soc-ph)Topology01 natural sciencesMeasure (mathematics)010305 fluids & plasmasSet (abstract data type)Development (topology)0103 physical sciences0202 electrical engineering electronic engineering information engineeringEquivalence (measure theory)Random graphSocial and Information Networks (cs.SI)Computer Science - Social and Information NetworksStatistical and Nonlinear PhysicsNetwork dynamicsPartition (database)[ INFO.INFO-OH ] Computer Science [cs]/Other [cs.OH]020201 artificial intelligence & image processingStatistics Probability and Uncertainty
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Identifying Causal Effects with the R Package causaleffect

2017

Do-calculus is concerned with estimating the interventional distribution of an action from the observed joint probability distribution of the variables in a given causal structure. All identifiable causal effects can be derived using the rules of do-calculus, but the rules themselves do not give any direct indication whether the effect in question is identifiable or not. Shpitser and Pearl constructed an algorithm for identifying joint interventional distributions in causal models, which contain unobserved variables and induce directed acyclic graphs. This algorithm can be seen as a repeated application of the rules of do-calculus and known properties of probabilities, and it ultimately eit…

Statistics and ProbabilityFOS: Computer and information sciencesTheoretical computer sciencecausalityDistribution (number theory)C-componentComputer sciencecausal model02 engineering and technologyCausal structureMethodology (stat.ME)03 medical and health sciences0302 clinical medicinedo-calculusJoint probability distribution0202 electrical engineering electronic engineering information engineering030212 general & internal medicineDAG; do-calculus; causality; causal model; identifiability; graph; C-component; hedge; d-separationlcsh:Statisticslcsh:HA1-4737Statistics - Methodologycomputer.programming_languageCausal modelta112DAGd-separationgraphhedgeidentifiabilityExpression (mathematics)PEARL (programming language)Action (philosophy)kausaliteetti020201 artificial intelligence & image processingStatistics Probability and UncertaintycomputerSoftware
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Statistics in Education

2015

During the last few decades, educational systems have attracted a great deal of interest because they are closely related to economic and social systems. For example, ‘higher education has been affected by a number of changes, including higher rates of participation, internationalization, the growing importance of knowledge-led economies and increased global completion’ (Bologna Process, 1999). There is a worldwide need to include in the educational language new words and concepts such as assessment, evaluation, accountability, student performance, mobility, competitiveness as part of a new governance system

Statistics and ProbabilityHigher educationbusiness.industry02 engineering and technology01 natural sciences010104 statistics & probabilitySocial systemeducation statistical models indicators0202 electrical engineering electronic engineering information engineeringMathematics education020201 artificial intelligence & image processingSettore SECS-S/05 - Statistica SocialeSociology0101 mathematicsStatistics Probability and UncertaintybusinessEducational systemsJournal of Applied Statistics
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