Search results for " image processing."

showing 10 items of 2265 documents

Artificial Decision Maker Driven by PSO : An Approach for Testing Reference Point Based Interactive Methods

2018

Over the years, many interactive multiobjective optimization methods based on a reference point have been proposed. With a reference point, the decision maker indicates desirable objective function values to iteratively direct the solution process. However, when analyzing the performance of these methods, a critical issue is how to systematically involve decision makers. A recent approach to this problem is to replace a decision maker with an artificial one to be able to systematically evaluate and compare reference point based interactive methods in controlled experiments. In this study, a new artificial decision maker is proposed, which reuses the dynamics of particle swarm optimization f…

Computer sciencepäätöksentekomultiple criteria decision makingContext (language use)02 engineering and technologyMachine learningcomputer.software_genre01 natural sciencesMulti-objective optimizationoptimointi0202 electrical engineering electronic engineering information engineeringmultiobjective optimization0101 mathematicsToma de decisionespreference articulationparticle swarm optimizationbusiness.industryParticle swarm optimizationDecision makermonitavoiteoptimointiPreferenceMulti-objective optimization010101 applied mathematicsBenchmark (computing)020201 artificial intelligence & image processingArtificial intelligencebusinesscomputer
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Breast Ultra-Sound image segmentation: an optimization approach based on super-pixels and high-level descriptors

2015

International audience; Breast cancer is the second most common cancer and the leading cause of cancer death among women. Medical imaging has become an indispensable tool for its diagnosis and follow up. During the last decade, the medical community has promoted to incorporate Ultra-Sound (US) screening as part of the standard routine. The main reason for using US imaging is its capability to differentiate benign from malignant masses, when compared to other imaging techniques. The increasing usage of US imaging encourages the development of Computer Aided Diagnosis (CAD) systems applied to Breast Ultra-Sound (BUS) images. However accurate delineations of the lesions and structures of the b…

ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONCAD02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingBI-RADS lexiconOptimization based Segmentation030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicineBreast cancerCut0202 electrical engineering electronic engineering information engineeringMedical imagingMedicineComputer visionBreast ultrasound[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingPixelmedicine.diagnostic_testbusiness.industryBreast Ultra-SoundGraph-CutsImage segmentationmedicine.disease3. Good healthComputingMethodologies_PATTERNRECOGNITIONComputer-aided diagnosis020201 artificial intelligence & image processingMachine-Learning based SegmentationArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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HDR-ARtiSt: A 1280x1024-pixel Adaptive Real-time Smart camera for High Dynamic Range video

2014

International audience; Standard cameras capture only a fraction of the information that is visible to the human visual system. This is specifically true for natural scenes including areas of low and high illumination due to transitions between sunlit and shaded areas. When capturing such a scene, many cameras are unable to store the full Dynamic Range (DR) resulting in low quality video where details are concealed in shadows or washed out by sunlight.The imaging technique that can overcome this problem is called HDR (High Dynamic Range) imaging. This paper describes a complete smart camera built around a standard off-the-shelf LDR (Low Dynamic Range) sensor and a Virtex 6 FPGA board. This …

ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingComputingMethodologies_COMPUTERGRAPHICS
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An optimization approach to segment breast lesions in ultra-sound images using clinically validated visual cues

2015

International audience; As long as breast cancer remains the leading cause of cancer deaths among female population world wide, developing tools to assist radiologists during the diagnosis process is necessary. However, most of the technologies developed in the imaging laboratories are rarely integrated in this assessing process, as they are based on information cues differing from those used by clinicians. In order to grant Computer Aided Diagnosis (CAD) systems with these information cues when performing non-aided diagnosis, better segmentation strategies are needed to automatically produce accurate delineations of the breast structures. This paper proposes a highly modular and flexible f…

ComputingMethodologies_PATTERNRECOGNITIONBreast Ultra-SoundComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONGraph-CutsMachine-Learning based Segmentation[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingBI-RADS lexiconOptimization based Segmentation[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
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Concept Drift Detection Using Online Histogram-Based Bayesian Classifiers

2016

In this paper, we present a novel algorithm that performs online histogram-based classification, i.e., specifically designed for the case when the data is dynamic and its distribution is non-stationary. Our method, called the Online Histogram-based Naïve Bayes Classifier (OHNBC) involves a statistical classifier based on the well-established Bayesian theory, but which makes some assumptions with respect to the independence of the attributes. Moreover, this classifier generates a prediction model using uni-dimensional histograms, whose segments or buckets are fixed in terms of their cardinalities but dynamic in terms of their widths. Additionally, our algorithm invokes the principles of info…

Concept driftComputer sciencebusiness.industryBayesian probabilityPattern recognition02 engineering and technologycomputer.software_genreInformation theoryNaive Bayes classifierComputingMethodologies_PATTERNRECOGNITION020204 information systemsHistogram0202 electrical engineering electronic engineering information engineeringsort020201 artificial intelligence & image processingData miningArtificial intelligencebusinesscomputerClassifier (UML)Statistical classifier
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Fuzzy Control of Uncertain Nonlinear Systems with Numerical Techniques: A Survey

2019

This paper provides an overview of numerical methods in order to solve fuzzy equations (FEs). It focuses on different numerical methodologies to solve FEs, dual fuzzy equations (DFEs), fuzzy differential equations (FDEs) and partial fuzzy differential equations (PFDEs). The solutions which are produced by these equations are taken to be the controllers. This paper also analyzes the existence of the roots of FEs and some important implementation problems. Finally, several examples are reviewed with different methods.

Condensed Matter::Quantum GasesComputer scienceNumerical analysisFuzzy differential equations010103 numerical & computational mathematics02 engineering and technologyFuzzy control system01 natural sciencesFuzzy logicDual (category theory)Nonlinear systemComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATION0202 electrical engineering electronic engineering information engineeringApplied mathematics020201 artificial intelligence & image processing0101 mathematics
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Chebyshev’s Method on Projective Fluids

2020

We demonstrate the acceleration potential of the Chebyshev semi-iterative approach for fluid simulations in Projective Dynamics. The Chebyshev approach has been successfully tested for deformable bodies, where the dynamical system behaves relatively linearly, even though Projective Dynamics, in general, is fundamentally nonlinear. The results for more complex constraints, like fluids, with a particular nonlinear dynamical system, remained unknown so far. We follow a method describing particle-based fluids in Projective Dynamics while replacing the Conjugate Gradient solver with Chebyshev’s method. Our results show that Chebyshev’s method can be successfully applied to fluids and potentially…

Conjugate gradient solverComputer sciencesimulace tekutinanimationAcceleration (differential geometry)02 engineering and technologyDynamical systemChebyshev filternonlinear optimization0202 electrical engineering electronic engineering information engineeringanimaceProjective testnelineární optimalizaceprojektivní dynamikaconstraint-based simulationsimulace založená na omezeníMathematical analysis020207 software engineeringComputer Graphics and Computer-Aided DesignComputational MathematicsNonlinear systemprojective dynamicsParticle020201 artificial intelligence & image processingfluid simulationProjective dynamicsSoftware
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Optimization of flat area coverage under connectivity constraint in wireless sensor networks

2022

A wireless sensor network consists of a set of small autonomous units that interact via a network built by their communication modules. They observe their environment, capture information, then manage this information according to their computing and/or storage capacity. To effectively accomplish their task(s), they need to cover as much of the area of interest as possible. It is therefore essential to quantify the quality of their coverage. In this thesis, we therefore seek to best cover an area of interest, with a precise number of sensors. While taking into account the possible overlaps between sensors, we first deploy in a zone of regular dimensions and evaluate the exact coverage using…

ConnectivityGenetic AlgorithmConnectivitéAlgorithme génétiqueInternet des objets[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingRéseaux de capteurs sans filInternet Of ThingsCouverture de zoneWireless sensor networksArea Coverage
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Argumentation graphs with constraint-based reasoning for collaborative expertise

2018

International audience; Collaborative processes are very important in telemedicine domain since they allow for making right decisions in complex situations with multidisciplinary staff. When modelling these collaborative processes, some inconsistencies can appear. In semantic modelling (conceptual graphs), these inconsistencies are verified using constraints. In this work, collaborative processes are represented using an argumentation system modelled in a conceptual graph formalism where inconsistencies could be particular bad attack relation between arguments. To overcome these inconsistencies, two solutions are proposed. The first one is to weight the arguments evolving in the argumentati…

Constraint based reasoningmedical deontologyComputer Networks and CommunicationsComputer sciencedomain0206 medical engineeringMédecine humaine et pathologieArgumentation theory02 engineering and technologyInconsistenciesWeightingdecision makingArgumentation theoryAutreMultidisciplinary approachframeworksCredibilityconceptual graphs0202 electrical engineering electronic engineering information engineeringinconsistenciesCompetence (human resources)Health professionalsManagement scienceMedical deontology[INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO]decision-makingargumentation theory16. Peace & justice020601 biomedical engineeringWeightingassignmentConceptual graphsHardware and ArchitectureConceptual graph020201 artificial intelligence & image processingweightingteleexpertiseDecision makingpreference-based argumentationmanagement[SDV.MHEP]Life Sciences [q-bio]/Human health and pathologySoftwareFuture Generation Computer Systems
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A pattern recognition approach for peak prediction of electrical consumption

2016

Predicting and mitigating demand peaks in electrical networks has become a prevalent research topic. Demand peaks pose a particular challenge to energy companies because these are difficult to foresee and require the net to support abnormally high consumption levels. In smart energy grids, time-differentiated pricing policies that increase the energy cost for the consumers during peak periods, and load balancing are examples of simple techniques for peak regulation. In this paper, we tackle the task of predicting power peaks prior to their actual occurrence in the context of a pilot Norwegian smart grid network.

Consumption (economics)Computer sciencebusiness.industry020209 energyLoad balancing (electrical power)Pattern recognitionContext (language use)02 engineering and technologyComputer Science ApplicationsTheoretical Computer SciencePower (physics)Task (project management)Computational Theory and MathematicsArtificial IntelligencePattern recognition (psychology)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingThe InternetArtificial intelligencebusinessSoftwareEnergy (signal processing)Integrated Computer-Aided Engineering
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