Search results for "Segmentation"

showing 10 items of 674 documents

What is the meaning of ‘talent’ in the world of work?

2013

The ongoing confusion about the meaning of ‘talent’ within the world of work is hindering the establishment of widely accepted talent management theories and practices. The aim of this paper is to contribute to the literature on talent management by offering an indepth review of the talent concept within the specific context of the world of work, and proposing a framework for its conceptualization. We group different theoretical approaches to talent into ‘object’ (i.e., talent as natural ability; talent as mastery; talent as commitment; talent as fit) versus ‘subject’ approaches (i.e., talent as all people; talent as some people) and identify dynamics existing within and between them, as we…

High potentialsOrganizational Behavior and Human Resource ManagementHigh performersSubject (philosophy)Context (language use)GeneralLiterature_MISCELLANEOUSInformationSystems_GENERALTalent managementComputingMilieux_COMPUTERSANDEDUCATIONNatural (music)SociologyRecursos humans -- DesenvolupamentApplied PsychologyTalentComputingMilieux_THECOMPUTINGPROFESSIONConceptualizationWorkforce segmentationbusiness.industryObject (philosophy)ManagementTalent managementHuman resource managementEngineering ethics:Economia i organització d'empreses::Gestió i direcció [Àrees temàtiques de la UPC]businessMeaning (linguistics)Human Resource Management Review
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Hypergraph imaging: an overview

2002

Hypergraph theory as originally developed by Berge (Hypergraphe, Dunod, Paris, 1987) is a theory of finite combinatorial sets, modeling lot of problems of operational research and combinatorial optimization. This framework turns out to be very interesting for many other applications, in particular for computer vision. In this paper, we are going to survey the relationship between combinatorial sets and image processing. More precisely, we propose an overview of different applications from image hypergraph models to image analysis. It mainly focuses on the combinatorial representation of an image and shows the effectiveness of this approach to low level image processing; in particular to seg…

HypergraphTheoretical computer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processingImage segmentationEdge detectionScale spaceArtificial IntelligenceComputer Science::Computer Vision and Pattern RecognitionSignal ProcessingCombinatorial optimizationComputer Vision and Pattern RecognitionRepresentation (mathematics)SoftwareMathematicsofComputing_DISCRETEMATHEMATICSFeature detection (computer vision)MathematicsPattern Recognition
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Loyalty Formation for Different Customer Journey Segments

2019

The proliferation of new touchpoints empowers today's customers to design their own journey from search to purchase. To address this new complexity, we segment customers by their use of specific touchpoints in the customer journey, investigate the association of several covariates with segment membership, consider the rise of mobile devices as potential "game changers" of existing segments, and explore how the relationships among product satisfaction, journey satisfaction, customer inspiration, and customer loyalty differ across segments. Based on anticipated utility theory and using latent class analyses on large-scale data from two samples of 2,443 and 2,649 journeys, we identify five tim…

IMPACTWEBSITEmedia_common.quotation_subjectBRANDCustomer journeyINSPIRATIONPURCHASEPRODUCTBusiness studiesLoyalty business modelMarket segmentationSEARCH0502 economics and businessLoyaltyProduct (category theory)media_commonOmnichannel managementMarketingCustomer inspirationCustomer satisfaction05 social sciencesCustomer segmentationAdvertisingMODELTouchpointsMODERATING ROLEEXPERIENCE050211 marketingCustomer satisfactionBusinessTouchpointMobile device050203 business & managementJournal of Retailing
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A novel framework for MR image segmentation and quantification by using MedGA

2019

BACKGROUND AND OBJECTIVES: Image segmentation represents one of the most challenging issues in medical image analysis to distinguish among different adjacent tissues in a body part. In this context, appropriate image pre-processing tools can improve the result accuracy achieved by computer-assisted segmentation methods. Taking into consideration images with a bimodal intensity distribution, image binarization can be used to classify the input pictorial data into two classes, given a threshold intensity value. Unfortunately, adaptive thresholding techniques for two-class segmentation work properly only for images characterized by bimodal histograms. We aim at overcoming these limitations and…

ING-INF/06 - BIOINGEGNERIA ELETTRONICA E INFORMATICAAdaptive thresholding; Bimodal intensity distribution; Evolutionary computation; Image pre-processing; Magnetic Resonance imaging; Quantitative medical imagingComputer scienceAdaptive thresholdingImage ProcessingDecision MakingNeurosurgeryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONHealth InformaticsContext (language use)Adaptive thresholding; Bimodal intensity distribution; Evolutionary computation; Image pre-processing; Magnetic Resonance imaging; Quantitative medical imaging; Algorithms; Brain Neoplasms; Computer Simulation; Decision Making; Female; Humans; Image Processing Computer-Assisted; Leiomyoma; Neurosurgery; Radiosurgery; Software; Magnetic Resonance ImagingEvolutionary computationRadiosurgeryING-INF/05 - SISTEMI DI ELABORAZIONE DELLE INFORMAZIONI030218 nuclear medicine & medical imaging03 medical and health sciencesComputer-Assisted0302 clinical medicineHistogramQuantitative medical imagingmedicineImage Processing Computer-AssistedHumansSegmentationComputer SimulationHistogram equalizationmedicine.diagnostic_testLeiomyomaSettore INF/01 - Informaticabusiness.industryBrain NeoplasmsINF/01 - INFORMATICAMagnetic resonance imagingPattern recognitionImage segmentationThresholdingComputer Science ApplicationsBimodal intensity distributionImage pre-processingTransformation (function)Magnetic Resonance imagingFemaleArtificial intelligencebusiness030217 neurology & neurosurgeryAlgorithmsSoftware
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Computer-Assisted Approaches for Uterine Fibroid Segmentation in MRgFUS Treatments: Quantitative Evaluation and Clinical Feasibility Analysis

2019

Nowadays, uterine fibroids can be treated using Magnetic Resonance guided Focused Ultrasound Surgery (MRgFUS), which is a non-invasive therapy exploiting thermal ablation. In order to measure the Non-Perfused Volume (NPV) for treatment response assessment, the ablated fibroid areas (i.e., Region of Treatment, ROT) are manually contoured by a radiologist. The current operator-dependent methodology could affect the subsequent follow-up phases, due to the lack of result repeatability. In addition, this fully manual procedure is time-consuming, considerably increasing execution times. These critical issues can be addressed only by means of accurate and efficient automated Pattern Recognition ap…

ING-INF/06 - BIOINGEGNERIA ELETTRONICA E INFORMATICAmedicine.medical_specialtyTreatment responseUterine fibroidsComputer scienceMagnetic Resonance guided Focused Ultrasound Surgery0206 medical engineeringThermal ablation02 engineering and technologyClinical feasibility; Computer-assisted medical image segmentation; Magnetic resonance guided focused ultrasound surgery; Non-Perfused volume assessment; Pattern recognition; Uterine fibroidsPattern RecognitionClinical feasibilityING-INF/05 - SISTEMI DI ELABORAZIONE DELLE INFORMAZIONI030218 nuclear medicine & medical imagingMagnetic resonance guided focused ultrasound surgeryMagnetic Resonance guided Focused Ultrasound Surgery Uterine fibroids03 medical and health sciences0302 clinical medicineNon-Perfused Volume assessmentmedicineUterine fibroidSegmentationUterine fibroids Indexed keywordsSettore INF/01 - InformaticaComputer Science (all)INF/01 - INFORMATICAmedicine.disease020601 biomedical engineeringComputer-assisted medical image segmentation; Pattern Recognition; Magnetic Resonance guided Focused Ultrasound Surgery Uterine fibroids; Non-Perfused Volume assessment; Clinical feasibility;Decision Sciences (all)Pattern recognition (psychology)RadiologyUterine fibroidsComputer-assisted medical image segmentation
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How Do Viewers Spontaneously Segment Animated Diagrams of Mechanical and Biological Subject Matter?

2012

A challenges for learning from animated diagrams is to first parse the continuous flow of information into discrete event units. Inadequacies in this parsing process can prejudice the quality of the mental model constructed from the depiction. One approach that has been proposed for ameliorating such problems is for the designer to pre-segment the animation. However, the pre-segmentation techniques used tend to be either intuitive or based on an expert's understanding of the subject matter. Neither of these approaches takes proper account of the psychological processing that must occur for an external animation to be properly internalized. This poster reports a study of the processes that l…

Identification (information)ParsingMultimediaComputer scienceHuman–computer interactionProcess (engineering)Event (computing)DepictionSegmentationAnimationMacrocomputer.software_genrecomputer
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Benchmarking Wilms’ tumor in multisequence MRI data: why does current clinical practice fail? Which popular segmentation algorithms perform well?

2019

Wilms' tumor is one of the most frequent malignant solid tumors in childhood. Accurate segmentation of tumor tissue is a key step during therapy and treatment planning. Since it is difficult to obtain a comprehensive set of tumor data of children, there is no benchmark so far allowing evaluation of the quality of human or computer-based segmentations. The contributions in our paper are threefold: (i) we present the first heterogeneous Wilms' tumor benchmark data set. It contains multisequence MRI data sets before and after chemotherapy, along with ground truth annotation, approximated based on the consensus of five human experts. (ii) We analyze human expert annotations and interrater varia…

Image ProcessingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION610 Medicine & healthMachine learningcomputer.software_genre030218 nuclear medicine & medical imagingSet (abstract data type)03 medical and health sciences0302 clinical medicineMedical imagingMedicineRadiology Nuclear Medicine and imagingSegmentationRadiation treatment planningbusiness.industry10042 Clinic for Diagnostic and Interventional RadiologyWilms' tumorBenchmarkingImage segmentationmedicine.disease3. Good healthComputingMethodologies_PATTERNRECOGNITION030220 oncology & carcinogenesisBenchmark (computing)Artificial intelligencebusinesscomputerJournal of Medical Imaging
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Image analysis for detecting aggregate gradation in asphalt mixture from planar images

2012

Abstract The mechanical properties of bituminous mixture strongly depend on the gradation of the aggregate that represents the mineral skeleton of the mixture, since for open and gap-graded mixtures, stresses due to vehicles in movement on the pavement are mainly transmitted through their contacts. Internal structure of bituminous mixture is, therefore, of great interest for road and infrastructure engineering and it is appropriate to study it with recently developed image analysis method. The purpose of this study was to finalize an effective analysis of asphalt section image for automatically extracting aggregate gradation without the need of separation of the bitumen from the aggregate. …

Image analysis Segmentation techniques Asphalt mixture Gradation controlMaterials scienceAggregate (composite)business.industryBuilding and ConstructionImage (mathematics)Digital imagePlanarAsphaltSettore ICAR/04 - Strade Ferrovie Ed AeroportiGeneral Materials ScienceSegmentationGradationGeotechnical engineeringProcess engineeringbusinessAnalysis methodCivil and Structural EngineeringConstruction and Building Materials
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Atlas selection strategy using least angle regression in multi-atlas segmentation propagation

2011

International audience; In multi-atlas based segmentation propagation, segmentations from multiple atlases are propagated to the target image and combined to produce the segmentation result. Local weighted voting (LWV) method is a classifier fusion method which combines the propagated atlases weighted by local image similarity. We demonstrate that the segmentation accuracy using LWV improves as the number of atlases increases. Under this context, we show that introducing diversity in addition to image similarity by using least-angle regression (LAR) criteria is a more efficient way to rank and select atlases. The accuracy of multi-atlas segmentation converges faster when the atlases are sel…

Image fusionContextual image classificationbusiness.industryAtlas (topology)Computer scienceLeast-angle regressionFeature extractionPattern recognitionImage segmentation030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicine[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV][INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV][ INFO.INFO-TI ] Computer Science [cs]/Image ProcessingSegmentationComputer visionArtificial intelligencebusiness030217 neurology & neurosurgery
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Image Segmentation by Deep Community Detection Approach

2017

International audience; To address the problem of segmenting an image into homogeneous communities this paper proposes an efficient algorithm to detect deep communities in the image by maximizing at each stage a new centrality measure, called the local Fiedler vector centrality (LFVC). This measure is associated with the sensitivity of algebraic connectivity to node removals. We show that a greedy node removal strategy, based on iterative maximization of LFVC, has bounded performance loss relative to the optimal, but intractable, combinatorial batch removal strategy. A remarkable feature of this method is the ability to segments the image automatically into homogeneous regions by maximizing…

Image segmentationAlgebraic connectivitybusiness.industrySegmentation-based object categorizationComputer scienceNode (networking)Complex networksScale-space segmentationLocal Fiedler vector centrality020206 networking & telecommunicationsPattern recognition02 engineering and technologyImage segmentation[INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI]Removal strategyFeature (computer vision)0202 electrical engineering electronic engineering information engineeringDeep community detection020201 artificial intelligence & image processingSegmentationArtificial intelligencebusinessCentrality
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