Search results for "Image"

showing 10 items of 6818 documents

Accurate estimation of retinal vessel width using bagged decision trees and an extended multiresolution Hermite model.

2012

We present an algorithm estimating the width of retinal vessels in fundus camera images. The algorithm uses a novel parametric surface model of the cross-sectional intensities of vessels, and ensembles of bagged decision trees to estimate the local width from the parameters of the best-fit surface. We report comparative tests with REVIEW, currently the public database of reference for retinal width estimation, containing 16 images with 193 annotated vessel segments and 5066 profile points annotated manually by three independent experts. Comparative tests are reported also with our own set of 378 vessel widths selected sparsely in 38 images from the Tayside Scotland diabetic retinopathy scre…

Accurate estimationComputer scienceStability (learning theory)Decision treeHealth Informaticscomputer.software_genreSensitivity and SpecificityPattern Recognition AutomatedSet (abstract data type)Parametric surfaceImage Interpretation Computer-AssistedHumansRadiology Nuclear Medicine and imagingFluorescein AngiographyHermite polynomialsDiabetic RetinopathySettore INF/01 - InformaticaRadiological and Ultrasound TechnologyReproducibility of ResultsRetinal VesselsImage EnhancementComputer Graphics and Computer-Aided DesignData setComputer Vision and Pattern RecognitionData miningRetinal images Vessel width Multiresolution Hermite model Ensembles of bagged decision trees Medical image analysiscomputerAlgorithmsTest dataRetinoscopyMedical image analysis
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Wooden panel paintings investigation: An air-coupled ultrasonic imaging approach

2007

In this paper, a method for the study of wooden panel paintings using air-coupled acoustical imaging is presented. In order to evaluate the advantages of the technique, several samples were made to mimic panel paintings along with their typical defects. These specimens were tested by means of both single-sided and through-transmission techniques using planar transducers. Image data were processed by means of a two-dimensional (2-D)-fast Fourier transform-based algorithm to increase the S/N ratio and 2-D representations (C-scans) were generated. The simulated defects were imaged using both configurations. Investigations were undertaken on four antique paintings from a private collection. The…

Acoustical imagingEngineeringAcoustics and Ultrasonicsbusiness.industryAirFast Fourier transformImage processingStructural engineeringWoodUltrasonic imagingsymbols.namesakeFourier transformNondestructive testingImage Interpretation Computer-AssistedMaterials TestingsymbolsPaintingsElectrical and Electronic EngineeringAir coupledbusinessInstrumentationAlgorithmsUltrasonographyIEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control
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Air-Coupled Imaging Method Applied to the Study and Conservation of Paintings

2007

An air-coupled acoustical imaging method for the study of wooden panel paintings is presented. After a brief overview of the state of the art, an introduction is given regarding the production technique of the art object under investigation. The technology employed is described in detail, as well as the proposed method. After a feasibility campaign of experiments, real ancient paintings have been investigated by means of a through-transmission and a single-sided lay-out. Defects were imaged in all the objects examined and in both the configurations adopted

Acoustical imagingPaintingComputer graphics (images)media_common.quotation_subjectComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONArtAir coupledObject (philosophy)GeneralLiterature_MISCELLANEOUSVisual artsmedia_common
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Combining gestures and vocalizations to imitate sounds

2015

International audience; Communicating about sounds is a difficult task without a technical language, and naïve speakers often rely on different kinds of non-linguistic vocalizations and body gestures (Lemaitre et al. 2014). Previous work has independently studied how effectively people describe sounds with gestures or vocalizations (Caramiaux, 2014, Lemaitre and Rocchesso, 2014). However, speech communication studies suggest a more intimate link between the two processes (Kendon, 2004). Our study thus focused on the combination of manual gestures and non-speech vocalizations in the communication of sounds. We first collected a large database of vocal and gestural imitations of a variety of …

Acoustics and UltrasonicsComputer scienceInformationSystems_INFORMATIONINTERFACESANDPRESENTATION(e.g.HCI)Speech recognition02 engineering and technologyRepresentation (arts)[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing[INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE][INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]Loudness[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI][SCCO]Cognitive science0202 electrical engineering electronic engineering information engineering[ INFO.INFO-NE ] Computer Science [cs]/Neural and Evolutionary Computing [cs.NE]050107 human factorsComputingMilieux_MISCELLANEOUSSound (medical instrument)05 social sciences[ SHS.ANTHRO-SE ] Humanities and Social Sciences/Social Anthropology and ethnology[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA][ SCCO.COMP ] Cognitive science/Computer science[SCCO.PSYC] Cognitive science/Psychology[INFO.INFO-SD]Computer Science [cs]/Sound [cs.SD][ SCCO.NEUR ] Cognitive science/Neuroscience[SCCO.PSYC]Cognitive science/Psychology[ INFO.EIAH ] Computer Science [cs]/Technology for Human Learning[ INFO.INFO-MA ] Computer Science [cs]/Multiagent Systems [cs.MA][INFO.EIAH]Computer Science [cs]/Technology for Human Learning[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingGesture[ SHS.MUSIQ ] Humanities and Social Sciences/Musicology and performing artsAcoustics[SCCO.COMP]Cognitive science/Computer scienceArts and Humanities (miscellaneous)[ INFO.INFO-HC ] Computer Science [cs]/Human-Computer Interaction [cs.HC]0501 psychology and cognitive sciences[ INFO.INFO-CL ] Computer Science [cs]/Computation and Language [cs.CL][INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC]Set (psychology)[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI][SPI.ACOU]Engineering Sciences [physics]/Acoustics [physics.class-ph][SPI.ACOU] Engineering Sciences [physics]/Acoustics [physics.class-ph][SHS.MUSIQ]Humanities and Social Sciences/Musicology and performing arts[ INFO.INFO-ET ] Computer Science [cs]/Emerging Technologies [cs.ET][SCCO.NEUR]Cognitive science/Neuroscience020207 software engineering[SHS.ANTHRO-SE]Humanities and Social Sciences/Social Anthropology and ethnologyVariety (linguistics)loudness[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET]Noise (video)[ INFO.INFO-SD ] Computer Science [cs]/Sound [cs.SD]
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Archetypal analysis: an alternative to clustering for unsupervised texture segmentation

2019

Texture segmentation is one of the main tasks in image applications, specifically in remote sensing, where the objective is to segment high-resolution images of natural landscapes into different cover types. Often the focus is on the selection of discriminant textural features, and although these are really fundamental, there is another part of the process that is also influential, partitioning different homogeneous textures into groups. A methodology based on archetype analysis (AA) of the local textural measurements is proposed. AA seeks the purest textures in the image and it can find the borders between pure textures, as those regions composed of mixtures of several archetypes. The prop…

Acoustics and UltrasonicsComputer scienceMaterials Science (miscellaneous)General MathematicsComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technologylocal granulometriesMathematical morphology01 natural sciencesTexture (geology)archetypeImage (mathematics)010104 statistics & probability0202 electrical engineering electronic engineering information engineeringRadiology Nuclear Medicine and imagingSegmentationmathematical morphology0101 mathematicsCluster analysisInstrumentationimage segmentationtexture analysislcsh:R5-920business.industrylcsh:MathematicsPattern recognitionImage segmentationlcsh:QA1-939DiscriminantSignal Processing020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionArtificial intelligenceFocus (optics)businesslcsh:Medicine (General)Biotechnology
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Automatic detection and classification of retinal vascular landmarks

2014

The main contribution of this paper is introducing a method to distinguish between different landmarks of the retina: bifurcations and crossings. The methodology may help in differentiating between arteries and veins and is useful in identifying diseases and other special pathologies, too. The method does not need any special skills, thus it can be assimilated to an automatic way for pinpointing landmarks; moreover it gives good responses for very small vessels. A skeletonized representation, taken out from the segmented binary image (obtained through a preprocessing step), is used to identify pixels with three or more neighbors. Then, the junction points are classified into bifurcations or…

Acoustics and UltrasonicsComputer scienceMaterials Science (miscellaneous)General MathematicsPreprocessorRadiology Nuclear Medicine and imagingComputer visionretinal vessel landmark points retinal vessel structure classificationRepresentation (mathematics)Instrumentationlcsh:R5-920PixelSettore INF/01 - Informaticabusiness.industryBinary imagelcsh:Mathematicslcsh:QA1-939retinal vessel structure classificationSignal ProcessingComputer Vision and Pattern RecognitionArtificial intelligencebusinessPrecision and recallretinal vessel landmark pointslcsh:Medicine (General)Biotechnology
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Comparing identification of vocal imitations and computational sketches of everyday sounds

2016

International audience; Sounds are notably difficult to describe. It is thus not surprising that human speakers often use many imitative vocalizations to communicate about sounds. In practice,vocal imitations of non-speech everyday sounds (e.g. the sound of a car passing by) arevery effective: listeners identify sounds better with vocal imitations than with verbal descriptions, despite the fact that vocal imitations are often inaccurate, constrained by the human vocal apparatus. The present study investigated the semantic representations evoked by vocal imitations by experimentally quantifying how well listeners could match sounds to category labels. Itcompared two different types of sounds…

Acoustics and UltrasonicsComputer science[ SHS.MUSIQ ] Humanities and Social Sciences/Musicology and performing artsSpeech recognitionAcoustics[SCCO.COMP]Cognitive science/Computer science[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing[INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE][INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL][INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI][SPI]Engineering Sciences [physics][SCCO]Cognitive scienceArts and Humanities (miscellaneous)[ INFO.INFO-HC ] Computer Science [cs]/Human-Computer Interaction [cs.HC][ INFO.INFO-CL ] Computer Science [cs]/Computation and Language [cs.CL][INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC][ INFO.INFO-NE ] Computer Science [cs]/Neural and Evolutionary Computing [cs.NE][ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]ComputingMilieux_MISCELLANEOUSSound (medical instrument)[ INFO.INFO-ET ] Computer Science [cs]/Emerging Technologies [cs.ET][SHS.MUSIQ]Humanities and Social Sciences/Musicology and performing arts[SCCO.NEUR]Cognitive science/Neuroscience[SHS.ANTHRO-SE]Humanities and Social Sciences/Social Anthropology and ethnologyIdentification (information)[ SHS.ANTHRO-SE ] Humanities and Social Sciences/Social Anthropology and ethnology[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA][ SCCO.COMP ] Cognitive science/Computer science[ SCCO.NEUR ] Cognitive science/Neuroscience[INFO.INFO-SD]Computer Science [cs]/Sound [cs.SD][ INFO.EIAH ] Computer Science [cs]/Technology for Human Learning[ INFO.INFO-MA ] Computer Science [cs]/Multiagent Systems [cs.MA][INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET][INFO.EIAH]Computer Science [cs]/Technology for Human Learning[ INFO.INFO-SD ] Computer Science [cs]/Sound [cs.SD][SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Mini-COVIDNet: Efficient Lightweight Deep Neural Network for Ultrasound Based Point-of-Care Detection of COVID-19

2021

Lung ultrasound (US) imaging has the potential to be an effective point-of-care test for detection of COVID-19, due to its ease of operation with minimal personal protection equipment along with easy disinfection. The current state-of-the-art deep learning models for detection of COVID-19 are heavy models that may not be easy to deploy in commonly utilized mobile platforms in point-of-care testing. In this work, we develop a lightweight mobile friendly efficient deep learning model for detection of COVID-19 using lung US images. Three different classes including COVID-19, pneumonia, and healthy were included in this task. The developed network, named as Mini-COVIDNet, was bench-marked with …

Acoustics and UltrasonicsCoronavirus disease 2019 (COVID-19)Computer sciencePoint-of-Care SystemsLatency (audio)detectionlung ultrasound (US) imaging01 natural sciences0103 physical sciencesImage Interpretation Computer-AssistedComputer-Assisted/methodsHumansElectrical and Electronic Engineering010301 acousticsInstrumentationImage InterpretationPoint of careUltrasonographyArtificial neural networkbusiness.industrySARS-CoV-2Deep learningImage Interpretation Computer-Assisted/methodsVDP::Technology: 500COVID-19deep learningUltrasonography/methodsLung ultrasoundCoronavirusTask (computing)point-of-care testingSoftware deploymentEmbedded systemCOVID-19/diagnostic imagingArtificial intelligencebusiness
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Estimation of fibre orientation from digital images

2001

In this paper, estimation of fibre orientation is studied for fibre systems observable as a blurred greyscale image. The estimation method is based on scaled variograms observed along a set of sampling lines in different directions. The parameters of the orientation distribution are obtained numerically. Simulated data are used to study the statistical properties of the method.

Acoustics and UltrasonicsMaterials Science (miscellaneous)General MathematicsGrayscaleSet (abstract data type)Digital imageimage analysisRadiology Nuclear Medicine and imagingComputer visionInstrumentationMathematicslcsh:R5-920Boolean modelbusiness.industryOrientation (computer vision)lcsh:MathematicsSampling (statistics)Boolean modelObservablesimulationlcsh:QA1-939Distribution (mathematics)fibre orientationdigitizationComputer Science::Computer Vision and Pattern RecognitionSignal ProcessingstereologyComputer Vision and Pattern RecognitionArtificial intelligencebusinesslcsh:Medicine (General)Biotechnology
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Control of irregular cardiac rhythm

2018

International audience; The aim of this work is to investigate the chaos control of the one di- mensional map which modelizes the duration of the current cardiac action potential (APD) as a function of the previous one. Using OGY control method, we obtain very satisfactory numerical results to stabilize the irregular heart rhythm into the normal rhythm.

Action Potential Duration (APD)chaos[MATH.MATH-DS]Mathematics [math]/Dynamical Systems [math.DS][ MATH.MATH-DS ] Mathematics [math]/Dynamical Systems [math.DS][MATH.MATH-DS] Mathematics [math]/Dynamical Systems [math.DS][ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing[ SDV.MHEP.CSC ] Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular systemequilibrium point[SDV.MHEP.CSC] Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system[SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular systemnormal rhythmirregular heart rhythm[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingcontrol[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
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