Search results for "Image."

showing 10 items of 6790 documents

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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Automatic Segmentation of HEp-2 Cells Based on Active Contours Model

2018

In the past years, a great deal of effort was put into research regarding Indirect Immunofluorescence techniques with the aim of development of CAD systems. In this work a method for segmenting HEp-2 cells in IIF images is presented. Such task is one of the most challenging of automated IIF analysis, because the segmentation algorithm has to cope with a large heterogeneity of shapes and textures. In order to address this problem, numerous techniques and their combinations were evaluated, in a process aimed at maximizing the figure of merit. The proposed method, for a greater definition of cellular contours, uses the active contours in the last phase of the process. The initial conditions, c…

Active contour modelComputer sciencebusiness.industryHEp-2 cellComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONProcess (computing)Pattern recognitionEllipseDice indexSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Hough transformlaw.inventionRandomized Hough transformHough transformlawPosition (vector)Convergence (routing)SegmentationArtificial intelligencebusinessActive contours modelCells segmentationIIF imagesProceedings of the 2018 3rd International Conference on Biomedical Imaging, Signal Processing
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253. An accurate and operator independent method for biological tumour volume segmentation

2018

Purpose The aim of this paper is to develop an operator independent method for biological tumour volume (BTV) delineation from Positron Emission Tomography (PET) images. BTV delineation is challenging because of the low spatial resolution and high noise level in PET images. In addition, BTV varies substantially depending on the method used to segment. Manual delineation is widely-used, but it is strongly user dependent. Methods The proposed method starts with the automatic identification of the PET slice with maximum Standardized Uptake Value (SUV). Then, a user- independent mask is obtained by a rough pre-segmentation step and it is used to perform the local active contour segmentation on …

Active contour modelSimilarity (geometry)medicine.diagnostic_testComputer sciencebusiness.industryBiophysicsGeneral Physics and AstronomyContext (language use)Pattern recognitionStandardized uptake valueGeneral MedicineImaging phantomPositron emission tomographymedicineRadiology Nuclear Medicine and imagingSegmentationArtificial intelligencebusinessImage resolutionPhysica Medica
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