Search results for "pattern"

showing 10 items of 4203 documents

Hyperspectral Texture Metrology Based on Joint Probability of Spectral and Spatial Distribution

2021

International audience; Texture characterization from the metrological point of view is addressed in order to establish a physically relevant and directly interpretable feature. In this regard, a generic formulation is proposed to simultaneously capture the spectral and spatial complexity in hyperspectral images. The feature, named relative spectral difference occurrence matrix (RSDOM) is thus constructed in a multireference, multidirectional, and multiscale context. As validation, its performance is assessed in three versatile tasks. In texture classification on HyTexiLa, content-based image retrieval (CBIR) on ICONES-HSI, and land cover classification on Salinas, RSDOM registers 98.5% acc…

Hyperspectral imagingbusiness.industryComputer scienceFeature extractionHyperspectral imagingPattern recognitionContext (language use)15. Life on landComputer Graphics and Computer-Aided DesignSupport vector machineGabor filtermetrologyJoint probability distributionFeature (computer vision)[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]Artificial intelligencebusinessImage retrievaltextureSoftware
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Comparing local structures of spatio-temporal point processes on linear networks

2022

We employ the Local Indicators of Spatio-Temporal Association (LISTA) functions on linear networks to build a statistical test for local second-order structure. This allows to identify differences in the spatio-temporal clustering behaviour of two point patterns, a point pattern of interest and a background one, both occurring on the same linear network. We illustrate the proposed methodology analysing a traffic-related problem.

Hypothesis testing Linear networks Local Indicators of Spatio-Temporal Association Local properties Second-order characteristics Spatio-temporal point patternsSettore SECS-S/01 - Statistica
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Robust H∞ filtering for networked control systems with markovian jumps and packet dropouts

2014

Published version of an article in the journal: Modeling, Identification and Control. Also available from the publisher at: http://dx.doi.org/10.4173/mic.2014.3.3 Open Access This paper deals with the H∞ filtering problem for uncertain networked control systems. In the study, network-induced delays, limited communication capacity due to signal quantization and packet dropout are all taken into consideration. The finite distributed delays with probability of occurrence in a random way is introduced in the network.The packet dropout is described by a Bernoulli process. The system is modeled as Markovian jumps system with partially known transition probabilities. A full-order filter is designe…

H∞ filterNetwork packetComputer scienceMarkov processComputer Science Applications1707 Computer Vision and Pattern RecognitionNetworked control systemMarkov jump systemH-Infinity filterH filterVDP::Mathematics and natural science: 400::Mathematics: 410::Analysis: 411lcsh:QA75.5-76.95Computer Science Applicationssymbols.namesakeIdentification (information)Markovian jumpControl and Systems EngineeringControl theorypacket dropoutsH∞ filter; Markov jump system; Networked control system; Packet dropouts; Control and Systems Engineering; Software; Modeling and Simulation; Computer Science Applications1707 Computer Vision and Pattern RecognitionModeling and SimulationControl systemsymbolslcsh:Electronic computers. Computer sciencenetworked control systemSoftware
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Mining travel patterns from mobile ticket applications

2014

Masteroppgave i Informasjons- og kommunikasjonsteknologi IKT590 Universitetet i Agder 2014 Customers’ travel patterns are highly interesting for transportation companies due tothe insight it gives over the use for their services. Logs of the customers’ location datais an important source for such companies. However, such data is not collected and isprivately owned by the individual customers. To find the customers’ travel patterns,their location data requires to match a coded map of transportation network.This paper introduces a novel solution that automatically collects location and timedata from the customers without the need for the customers to actively submit thedata. This paper presen…

IKT590travel patterns ; mining ; mobile ticket applicationsVDP::Technology: 500::Information and communication technology: 550
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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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A Civilization of Death: Argumentative and Rhetorical Strategies in the Catholic Church's Position on Biotechnology

2017

Although political deliberation rarely proceeds fairly and effectively (Habermas 1984, 1989), the author of this paper assumes the fundamentally deliberative nature of the democratic public sphere, in which different religious institutions may take a stance and argue either for or against certain legal solutions. The study examines argumentation behind the Catholic Church’s negative stance on biotechnologies such as, for example, in vitro fertilization (IVF). Drawing on the theoretical and descriptive work on normative assumptions, knowledge bases and argumentative patterns involved in practical reasoning (Perelman, Olbrechts- Tyteca 1969; Walton 1990; Fairclough, Fairclough 2010, 2012), as…

IVF debateargumentative patternspolitical discoursepublic debate
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Identification of parameters of the Jiles-Atherton model by neural networks

2011

In this paper a procedure for the identification of the parameters of the Jiles–Atherton (JA) model is presented. The parameters of the JA model of a material are found by using a neural network trained by a collection of hysteresis curves, whose parameters are known. After a presentation of the Jiles–Atherton model, the neural network and the training procedure are described and the method is validated by using some numerical, as well as experimental, data.

Identification (information)HysteresisProbabilistic neural networkArtificial neural networkbusiness.industryComputer scienceMagnetic hysteresis neural nets physics computingJiles-Atherton modelGeneral Physics and AstronomyPattern recognitionArtificial intelligencebusiness
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Patterns and determinants of adherence to resistance and endurance training during cancer treatment in the Phys-Can RCT.

2022

Abstract Background Knowledge regarding adherence is necessary to improve the specificity of exercise interventions during cancer treatment. We aimed to determine adherence to resistance and endurance training interventions in parallel; identify subgroups with similar adherence characteristics; and examine determinants of these subgroups. Methods In the Phys-Can randomised controlled trial, participants (n = 577, 81% women, mean(SD) age 59(12) years, and 50% with BMI ≥ 25 kg/m2) starting (neo-) adjuvant treatment for breast, colorectal or prostate cancer were randomized to 6-month of high (HI) or low-to-moderate intensity (LMI) supervised, group-based resistance training and individual home…

IdrottsvetenskapRehabilitationPhysical Therapy Sports Therapy and RehabilitationResistance trainingEndurance trainingTumours of the digestive tract Radboud Institute for Health Sciences [Radboudumc 14]All institutes and research themes of the Radboud University Medical CenterAdherenceFITT principlesOrthopedics and Sports MedicineVDP::Medisinske Fag: 700PatternsExerciseDeterminantsSport and Fitness SciencesCancerBMC sports science, medicinerehabilitation
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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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