Search results for "Intelligence"

showing 10 items of 6959 documents

Accommodative Stimulus-Response Curve with Emoji Symbols

2017

Purpose. To evaluate the static measurement of the accommodative stimulus-response curve with emoji symbols. Methods. The accommodative stimulus-response curve was measured in 18 subjects using a Hartmann-Shack sensor to obtain the objective accommodative response from the Zernike defocus term. Measurements were acquired at different accommodative demands, from 0 to 3 D with a step of 0.5 D. Detailed and nondetailed emoji targets were used with two different sizes, corresponding to the two most common visual angles used in smartphones. Results. A regression analysis was performed to fit the mean results obtained for each target. The determination coefficient was R2≥0.988 for all targets. Fo…

Accommodative responseArticle SubjectZernike polynomialsEmojibusiness.industryRegression analysisPattern recognitionTerm (time)Stimulus response03 medical and health sciencesOphthalmologysymbols.namesake0302 clinical medicinelcsh:Ophthalmologylcsh:RE1-994030221 ophthalmology & optometrysymbolsMedicineComputer visionArtificial intelligencebusiness030217 neurology & neurosurgeryWord (computer architecture)Research ArticleJournal of Ophthalmology
researchProduct

A comparison among different techniques for human ERG signals processing and classification

2014

A comparison among different techniques for human ERG signals processing and classification ( Articles not published yet, but available online Article in press About articles in press (opens in a new window) ) Barraco, R.a, Persano Adorno, D.a , Brai, M.a, Tranchina, L.b a Dipartimento di Fisica e Chimica, Università di Palermo and CNISM, Viale delle Scienze, Ed. 18, I-90128 Palermo, Italy b Laboratorio di Fisica e Tecnologie Relative - UniNetLab, Università di Palermo, Viale delle Scienze, Ed. 18, I-90128 Palermo, Italy Abstract Feature detection in biomedical signals is crucial for deepening our knowledge about the involved physiological processes. To achieve this aim, many analytic appro…

Achromatopsiagenetic structuresComputer scienceBiophysicsGeneral Physics and AstronomyColor Vision DefectsPrincipal component analysiWavelet analysisPattern Recognition AutomatedWaveletRetinal pathologieElectroretinographymedicineHumansRadiology Nuclear Medicine and imagingComputer visionFeature detection (computer vision)Principal Component AnalysisSignal processingFourier Analysisbusiness.industryWavelet transformSignal Processing Computer-AssistedPattern recognitionGeneral Medicinemedicine.diseaseSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)eye diseasesERG signalClinical diagnosisPrincipal component analysissense organsArtificial intelligencebusinessErgPhysica Medica
researchProduct

Semantic structures of timbre emerging from social and acoustic descriptions of music

2011

The perceptual attributes of timbre have inspired a considerable amount of multidisciplinary research, but because of the complexity of the phenomena, the approach has traditionally been confined to laboratory conditions, much to the detriment of its ecological validity. In this study, we present a purely bottom-up approach for mapping the concepts that emerge from sound qualities. A social media ( http://www.last.fm ) is used to obtain a wide sample of verbal descriptions of music (in the form of tags) that go beyond the commonly studied concept of genre, and from this the underlying semantic structure of this sample is extracted. The structure that is thereby obtained is then evaluated th…

Acoustics and UltrasonicsComputer scienceEcological validityMusic information retrievalsointiväriSpeech recognitionmusiikkisosiaalinen mediacomputer.software_genreTimbreSimilarity (psychology)Social media.Music information retrievalElectrical and Electronic EngineeringSet (psychology)Structure (mathematical logic)Music psychologybusiness.industryNatural language processingVector-based semantic analysisDegree (music)acoustic featuresakustiset piirteetArtificial intelligencebusinessTimbrecomputerNatural language processingEURASIP Journal on Audio, Speech, and Music Processing
researchProduct

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]
researchProduct

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
researchProduct

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
researchProduct

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
researchProduct

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
researchProduct

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
researchProduct

Three-dimensional ultrasound radiance mode imaging of a uterine lipoleiomyoma.

2016

In this case report the diagnosis of a uterine lipoleiomyoma is depicted by means of a three-dimensional radiance mode. The advent of radiance or silhouette mode as a new tool in ultrasound diagnosis is intended to assist by generating additional realistic image visualization and a better distinction among different tissues.

Acoustics and UltrasonicsSilhouetteDiagnosis DifferentialImaging Three-DimensionalHumansMedicineRadiology Nuclear Medicine and imagingComputer vision3D ultrasoundUterine NeoplasmUltrasonographyThree dimensional ultrasoundLeiomyomaRadiological and Ultrasound Technologymedicine.diagnostic_testbusiness.industryUterusUltrasoundMode (statistics)Middle AgedVisualizationUterine NeoplasmsRadianceFemaleLipomaArtificial intelligencebusinessMedical Ultrasonography
researchProduct