Search results for " image processing."

showing 10 items of 2265 documents

Multi-Dimensional motivic pattern extraction founded on adaptive redundancy filtering

2005

Abstract We present a computational model for discovering repeated patterns in symbolic representations of monodic music. Patterns are discovered through an incremental adaptive identification along a multi-dimensional parametric space. The difficulties of pattern discovery mainly come from combinatorial redundancies, that our model is able to control efficiently. A specificity relation is defined between pattern descriptions, unifying suffix and inclusion relations and enabling a filtering of redundant descriptions. Combinatorial proliferation caused by successive repetitions of patterns is managed using cyclic patterns. The modelling of these redundancy control mechanisms enables an autom…

Theoretical computer scienceVisual Arts and Performing ArtsRelation (database)Space (commercial competition)050105 experimental psychology060404 music[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI][INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[STAT.ML]Statistics [stat]/Machine Learning [stat.ML][INFO.INFO-FL]Computer Science [cs]/Formal Languages and Automata Theory [cs.FL]Redundancy (engineering)0501 psychology and cognitive sciencesControl (linguistics)MathematicsParametric statistics[INFO.INFO-PL]Computer Science [cs]/Programming Languages [cs.PL][SHS.MUSIQ]Humanities and Social Sciences/Musicology and performing artsbusiness.industry05 social sciences06 humanities and the artsAutomation[INFO.INFO-SD]Computer Science [cs]/Sound [cs.SD]Multi dimensionalNASuffixbusiness0604 artsMusic
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New Representations for Multidimensional Functions Based on Kolmogorov Superposition Theorem. Applications on Image Processing

2012

Mastering the sorting of the data in signal (nD) can lead to multiple applications like new compression, transmission, watermarking, encryption methods and even new processing methods for image. Some authors in the past decades have proposed to use these approaches for image compression, indexing, median filtering, mathematical morphology, encryption. A mathematical rigorous way for doing such a study has been introduced by Andrei Nikolaievitch Kolmogorov (1903-1987) in 1957 and recent results have provided constructive ways and practical algorithms for implementing the Kolmogorov theorem. We propose in this paper to present those algorithms and some preliminary results obtained by our team…

Theoretical computer science[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processingbusiness.industry[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingSortingimage progressive transmissionImage processingimage encryption[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingMathematical morphologyEncryptionimage watermarkingimage compressionImage (mathematics)multi-variables function representation[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingKolmogorov superposition theoremMedian filterbusinessDigital watermarkingAlgorithm[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingImage compressionMathematics[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
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Representations for evolutionary algorithms

2015

Successful and efficient use of evolutionary algorithms (EA) depends on the choice of the genotype, the problem representation (mapping from genotype to phenotype) and on the choice of search operators that are applied to the genotypes. These choices cannot be made independently of each other. The question whether a certain representation leads to better performing EAs than an alternative representation can only be answered when the operators applied are taken into consideration. The reverse is also true: deciding between alternative operators is only meaningful for a given representation. In EA practice one can distinguish two complementary approaches. The first approach uses indirect repr…

Theoretical computer sciencebusiness.industryComputer scienceEvolutionary algorithmRepresentation (systemics)Genetic programming0102 computer and information sciences02 engineering and technologyComputingMethodologies_ARTIFICIALINTELLIGENCEPhenotype01 natural sciencesOperator (computer programming)Grammatical evolution010201 computation theory & mathematicsGenetic algorithmGenotype0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingGenetic representationArtificial intelligencebusinessProceedings of the Genetic and Evolutionary Computation Conference Companion
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E-learning approach of the graph coloring problem applied to register allocation in embedded systems

2016

The main aim of this paper consists in developing an effective e-learning tool, focused on evolutionary algorithms, in order to solve the graph coloring problem. Subsidiary, we apply graph coloring for register allocation in embedded systems. From didactic viewpoint, our tool has benefits in the learning process because it helps students to observe the relationship between the graph coloring problem and CPU registers allocation with the help of four developed modules: the genetic algorithm, the graphical viewer, the interference graph for a C program and a web application which collects the simulation results. All these applications are combined by a graphical interface which allows the use…

Theoretical computer sciencebusiness.industryComputer scienceProcessor registerEvolutionary algorithm02 engineering and technology021001 nanoscience & nanotechnologyEmbedded systemGenetic algorithm0202 electrical engineering electronic engineering information engineeringWeb applicationGraph (abstract data type)020201 artificial intelligence & image processingGraph coloring0210 nano-technologybusinessGraphical user interfaceRegister allocation2016 Sixth International Conference on Innovative Computing Technology (INTECH)
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Properties and constraints of cheating-immune secret sharing schemes

2006

AbstractA secret sharing scheme is a cryptographic protocol by means of which a dealer shares a secret among a set of participants in such a way that it can be subsequently reconstructed by certain qualified subsets. The setting we consider is the following: in a first phase, the dealer gives in a secure way a piece of information, called a share, to each participant. Then, participants belonging to a qualified subset send in a secure way their shares to a trusted party, referred to as a combiner, who computes the secret and sends it back to the participants.Cheating-immune secret sharing schemes are secret sharing schemes in the above setting where dishonest participants, during the recons…

TheoryofComputation_MISCELLANEOUSHomomorphic secret sharingCryptography0102 computer and information sciences02 engineering and technologyShared secretComputer securitycomputer.software_genre01 natural sciencesSecret sharingCheating0202 electrical engineering electronic engineering information engineeringDiscrete Mathematics and CombinatoricsSecret sharingMathematicsbusiness.industryApplied MathematicsCryptographic protocol16. Peace & justiceShamir's Secret Sharing010201 computation theory & mathematicsResilient functionsCryptographySecure multi-party computation020201 artificial intelligence & image processingVerifiable secret sharingbusinesscomputerDiscrete Applied Mathematics
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Improved Liquid Crystal Thermography by Using True-Colour Image Processing Technology

2002

No abstract available

Thermochromic Liquid CrystalDigital Image ProcessingThermographyHeat TransferSettore ING-IND/19 - Impianti Nucleari
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The Use of Thermochromic Liquid Crystals and Image Processing for Technical and Biomedical Thermography

1999

Thermochromic Liquid CrystalDigital Image ProcessingThermographyHeat TransferSettore ING-IND/19 - Impianti Nucleari
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A novel dynamic multi-model relevance feedback procedure for content-based image retrieval

2016

This paper deals with the problem of image retrieval in large databases with a big semantic gap by a relevance feedback procedure. We present a novel algorithm for modelling the users's preferences in the content-based image retrieval system.The proposed algorithm considers the probability of an image belonging to the set of those sought by the user, and estimates the parameters of several local logistic regression models whose inputs are the low-level image features. A Principal Component Analysis method is applied to the original vector to reduce its high dimensionality. The relevance probabilities predicted by these local models are combined by means of a weighted average. These weights …

Thesaurus (information retrieval)Computer scienceCognitive NeuroscienceRelevance feedback020207 software engineering02 engineering and technologycomputer.software_genreContent-based image retrievalComputer Science ApplicationsSet (abstract data type)Search engineArtificial IntelligenceFeature (computer vision)Principal component analysis0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingRelevance (information retrieval)Data miningcomputerImage retrievalSemantic gapNeurocomputing
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Inter-Model Consistency and Complementarity: Learning from ex-vivo Imaging and Electrophysiological Data towards an Integrated Understanding of Cardi…

2011

International audience; Computational models of the heart at various scales and levels of complexity have been independently developed, parameterised and validated using a wide range of experimental data for over four decades. However, despite remarkable progress, the lack of coordinated efforts to compare and combine these computational models has limited their impact on the numerous open questions in cardiac physiology. To address this issue, a comprehensive dataset has previously been made available to the community that contains the cardiac anatomy and fibre orientations from magnetic resonance imaging as well as epicardial transmembrane potentials from optical mapping measured on a per…

Time FactorsComputer scienceSwine[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/ImagingBiophysics030204 cardiovascular system & hematologyIn Vitro Techniquescomputer.software_genreModels BiologicalBiophysical PhenomenaPersonalizationMembrane PotentialsDiffusionPurkinje Fibers03 medical and health sciences0302 clinical medicine[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingOptical mappingMaximum a posteriori estimation[INFO.INFO-IM]Computer Science [cs]/Medical ImagingAnimalsMolecular Biology030304 developmental biology0303 health sciencesComputational modelCardiac electrophysiologybusiness.industryBiophysical PhenomenaExperimental dataReproducibility of ResultsHeartMagnetic Resonance Imaging[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationElectrophysiological PhenomenaSystems IntegrationSystem integrationArtificial intelligenceData miningbusinesscomputerPericardium[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Introduction to coronary imaging with 64-slice computed tomography

2005

The aim of this article is to illustrate the main technical improvements in the last generation of 64-row CT scanners and the possible applications in coronary angiography. In particular, we describe the new physical components (X-ray tube-detectors system) and the general scan and reconstruction parameters. We then define the scan protocols for coronary angiography with the new generation of 64-row CT scanners to enable radiologists to perform a CT study on the basis of the diagnostic possibilities.

Time FactorsImaging Sensitivity and Specificity Stents Time Factors TomographyContrast MediaSensitivity and Specificity64-row CTElectrocardiographyHeart RateSpiral Computed TomographyImage Processing Computer-AssistedHumanstechnical improvementsCoronary Artery BypassPhantoms ImagingPatient SelectionAlgorithms Artifacts Contrast Media Coronary Angiography/instrumentation/*methods Coronary Artery Bypass Coronary Stenosis/*radiography Electrocardiography Heart Rate Humans Image Processing; Computer-Assisted Patient Selection Phantoms; Imaging Sensitivity and Specificity Stents Time Factors Tomography; Spiral Computed Tomography; X-Ray Computed/instrumentation/*methodsCoronary StenosisComputer-Assisted Patient Selection PhantomsX-Ray Computed/instrumentation/*methodstechnical improvements; 64-row CT; coronary angiographyComputer-Assisted Patient Selection PhantomStentsAlgorithms Artifacts Contrast Media Coronary Angiography/instrumentation/*methods Coronary Artery Bypass Coronary Stenosis/*radiography Electrocardiography Heart Rate Humans Image Processingcoronary angiographyArtifactsTomography X-Ray ComputedTomography Spiral ComputedAlgorithms
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