Search results for "image processing"

showing 10 items of 3285 documents

Surrogate outcomes and transportability

2019

Identification of causal effects is one of the most fundamental tasks of causal inference. We consider an identifiability problem where some experimental and observational data are available but neither data alone is sufficient for the identification of the causal effect of interest. Instead of the outcome of interest, surrogate outcomes are measured in the experiments. This problem is a generalization of identifiability using surrogate experiments and we label it as surrogate outcome identifiability. We show that the concept of transportability provides a sufficient criteria for determining surrogate outcome identifiability for a large class of queries.

FOS: Computer and information scienceskokeilucausalityGeneralizationComputer scienceComputer Science - Artificial Intelligence02 engineering and technologyMachine learningcomputer.software_genreOutcome (game theory)Theoretical Computer ScienceMethodology (stat.ME)do-calculusArtificial Intelligence020204 information systemsalgoritmit0202 electrical engineering electronic engineering information engineeringStatistics - Methodologyta113päättelyta112experimentbusiness.industrySurrogate endpointverkkoteoriaApplied MathematicsCausal effectta111graphidentifiabilityIdentification (information)Artificial Intelligence (cs.AI)Causal inferencekausaliteettiIdentifiability020201 artificial intelligence & image processingObservational studyArtificial intelligencebusinessmediatorcomputerSoftware
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Fast PET Scan Tumor Segmentation Using Superpixels, Principal Component Analysis and K-Means Clustering

2018

Positron Emission Tomography scan images are extensively used in radiotherapy planning, clinical diagnosis, assessment of growth and treatment of a tumor. These all rely on fidelity and speed of detection and delineation algorithm. Despite intensive research, segmentation remained a challenging problem due to the diverse image content, resolution, shape, and noise. This paper presents a fast positron emission tomography tumor segmentation method in which superpixels are extracted first from the input image. Principal component analysis is then applied on the superpixels and also on their average. Distance vector of each superpixel from the average is computed in principal components coordin…

FOS: Computer and information sciencespositron emission tomographyprincipal component analysisComputer scienceComputer Vision and Pattern Recognition (cs.CV)k-meansCoordinate systemComputer Science - Computer Vision and Pattern RecognitionFOS: Physical sciences02 engineering and technologyBenchmarkQuantitative Biology - Quantitative MethodsBiochemistry Genetics and Molecular Biology (miscellaneous)030218 nuclear medicine & medical imagingsuperpixels03 medical and health sciences0302 clinical medicineStructural Biology0202 electrical engineering electronic engineering information engineeringmedicineSegmentationComputer visionTissues and Organs (q-bio.TO)Cluster analysisQuantitative Methods (q-bio.QM)Pixelmedicine.diagnostic_testbusiness.industrysegmentationk-means clusteringQuantitative Biology - Tissues and OrgansPattern recognitionPhysics - Medical PhysicsPositron emission tomographyFOS: Biological sciencesPhysics - Data Analysis Statistics and ProbabilityPrincipal component analysis020201 artificial intelligence & image processingMedical Physics (physics.med-ph)Artificial intelligenceNoise (video)businessData Analysis Statistics and Probability (physics.data-an)BiotechnologyMethods and Protocols
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Fast Estimation of Diffusion Tensors under Rician noise by the EM algorithm

2016

Diffusion tensor imaging (DTI) is widely used to characterize, in vivo, the white matter of the central nerve system (CNS). This biological tissue contains much anatomic, structural and orientational information of fibers in human brain. Spectral data from the displacement distribution of water molecules located in the brain tissue are collected by a magnetic resonance scanner and acquired in the Fourier domain. After the Fourier inversion, the noise distribution is Gaussian in both real and imaginary parts and, as a consequence, the recorded magnitude data are corrupted by Rician noise. Statistical estimation of diffusion leads a non-linear regression problem. In this paper, we present a f…

FOS: Computer and information sciencesreduced computationGaussianModels NeurologicalDatasets as Topicta3112Statistics - ComputationStatistics - ApplicationsTime030218 nuclear medicine & medical imagingMethodology (stat.ME)Diffusion03 medical and health sciencessymbols.namesake0302 clinical medicineScoring algorithmRician fadingPrior probabilityExpectation–maximization algorithmImage Processing Computer-AssistedMaximum a posteriori estimationHumansApplications (stat.AP)Computer SimulationComputation (stat.CO)Statistics - MethodologyMathematicsta112Likelihood FunctionsGeneral NeuroscienceBrainEstimatormaximum likelihood estimatorFisher scoringMagnetic Resonance ImagingWhite MatterRician likelihoodDiffusion Tensor ImagingFourier transformNonlinear Dynamicssymbolsmaximum a posteriori estimatorAlgorithmAlgorithms030217 neurology & neurosurgerydata augmentation
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Low-Power Audio Keyword Spotting using Tsetlin Machines

2021

The emergence of Artificial Intelligence (AI) driven Keyword Spotting (KWS) technologies has revolutionized human to machine interaction. Yet, the challenge of end-to-end energy efficiency, memory footprint and system complexity of current Neural Network (NN) powered AI-KWS pipelines has remained ever present. This paper evaluates KWS utilizing a learning automata powered machine learning algorithm called the Tsetlin Machine (TM). Through significant reduction in parameter requirements and choosing logic over arithmetic based processing, the TM offers new opportunities for low-power KWS while maintaining high learning efficacy. In this paper we explore a TM based keyword spotting (KWS) pipe…

FOS: Computer and information sciencesspeech commandSound (cs.SD)Computer scienceSpeech recognition02 engineering and technologykeyword spottingMachine learningcomputer.software_genreComputer Science - SoundReduction (complexity)Audio and Speech Processing (eess.AS)020204 information systemsFOS: Electrical engineering electronic engineering information engineering0202 electrical engineering electronic engineering information engineeringElectrical and Electronic EngineeringArtificial neural networkLearning automatabusiness.industrylearning automatalcsh:Applications of electric power020206 networking & telecommunicationslcsh:TK4001-4102Pipeline (software)Power (physics)machine learningTsetlin MachineMFCCKeyword spottingelectrical_electronic_engineeringScalabilityMemory footprintpervasive AI020201 artificial intelligence & image processingMel-frequency cepstrumArtificial intelligencebusinesscomputerartificial neural networkEfficient energy useElectrical Engineering and Systems Science - Audio and Speech Processing
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Estimation des performances, test et contrôle des systèmes cyber-physiques employant des réseaux de communication non idéaux

2020

Wireless technology is a key enabler of the promises of Industry 4.0 (Smart Manufacturing). As such, wireless technology will be adopted as a principal mode of communication within the factory beginning with the factory enterprise and eventually being adopted for use within the factory workcell. Factory workcell communication has particular requirements on latency, reliability, scale, and security that must first be met by the wireless communication technology used. Wireless is considered a non-ideal form of communication in that when compared to its wired counterparts, it is considered less reliable (lossy) and less secure. These possible impairments lead to delay and loss of data in indus…

Fabrication intelligenteIndustrial wireless testbed[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingSmart manufacturingApprentissage automatiqueSystems modelingGraph databaseBase de données graphe[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingMachine learningIndustrial wirelessModelisation systémeCommunications sans fil industrielBanc d'essai sans fil industriel
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Automatable sample fabrication process for pump-probe X-ray holographic imaging

2014

Soft X-ray holography is a recently developed imaging technique with sub-50 nm spatial resolution. Key advantages of this technique are magnetic and elemental sensitivity, compatibility with imaging at free electron laser facilities, and immunity to in-situ sample excitations and sample drift, which enables the reliable detection of relative changes between two images with a precision of a few nanometers. In X-ray holography, the main part of the experimental setup is integrated in the sample, which consequently requires a large number of fabrication steps. Here we present a generic design and an automatable fabrication process for samples suitable, and optimized for, efficient high resolut…

FabricationMaterials scienceImage qualityDynamic imagingHolographyComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONHolography02 engineering and technologyIterative reconstruction01 natural scienceslaw.inventionOpticslaw0103 physical sciencesDigital image processing010306 general physicsImage resolutionLithographybusiness.industryEquipment Design021001 nanoscience & nanotechnologyAtomic and Molecular Physics and OpticsEquipment Failure AnalysisComputer-Aided DesignRadiographic Image Interpretation Computer-Assisted0210 nano-technologybusinessOptics Express
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Automatic landmark detection and 3D Face data extraction

2017

Abstract This paper contributes to 3D facial synthesis by presenting a novel method for parameterization using Landmark Point detection. The approach presented aims at improving facial recognition even in varying facial expressions, and missing data in 3D facial models. As such, the prime objective was to develop an automatically embedded process that can detect any frontal face in 3D face recognition systems, with face segmentation and surface curvature information. Using the hybrid interpolation method, experiments on facial landmarks were performed on 4950 images from Face Recognition Grand Challenge database (FRGC). Distinctive facial landmarks from the nose–tips, Limits mouth and two e…

Face hallucinationGeneral Computer ScienceComputer sciencebusiness.industry05 social sciencesComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION050301 educationIterative closest pointPattern recognition02 engineering and technologyLandmark pointFace Recognition Grand ChallengeFacial recognition systemTheoretical Computer SciencePoint distribution modelModeling and Simulation0202 electrical engineering electronic engineering information engineeringThree-dimensional face recognition020201 artificial intelligence & image processingComputer visionArtificial intelligenceFace detectionbusiness0503 educationJournal of Computational Science
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Probabilistic Corner Detection for Facial Feature Extraction

2009

After more than 35 years of resarch, face processing is considered nowadays as one of the most important application of image analysis. It can be considered as a collection of problems (i.e., face detection, normalization, recognition and so on) each of which can be treated separately. Some face detection and face recognition techniques have reached a certain level of maturity, however facial feature extraction still represents the bottleneck of the entire process. In this paper we present a novel facial feature extraction approach that could be used for normalizing Viola-Jones detected faces and let them be recognized by an appearance-based face recognition method. For each observed featur…

Face hallucinationbusiness.industryComputer scienceFeature extractionCorner detectionNormalization (image processing)Pattern recognitionFace detection - face recognition - features extraction - CBIRFacial recognition systemObject-class detectionThree-dimensional face recognitionComputer visionArtificial intelligenceFace detectionbusiness
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Automatic Generation of Subject-Based Image Transitions

2011

This paper presents a novel approach for the automatic generation of image slideshows. Counter to standard cross-fading, the idea is to operate the image transitions keeping the subject focused in the intermediate frames by automatically identifying him/her and preserving face and facial features alignment. This is done by using a novel Active Shape Model and time-series Image Registration. The final result is an aesthetically appealing slideshow which emphasizes the subject. The results have been evaluated with a users’ response survey. The outcomes show that the proposed slideshow concept is widely preferred by final users w.r.t. standard image transitions.

Face processing; image morphing; image registrationComputer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage registrationSubject (documents)Image processingimage morphingImage (mathematics)image registrationAutomatic image annotationActive shape modelFace (geometry)Face processingComputer visionArtificial intelligencebusinessFeature detection (computer vision)
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Facet braiding: a fundamental problem in integral imaging.

2007

A rigorous explanation of a phenomenon that produces significant distortions in the three-dimensional images produced by integral imaging systems is provided. The phenomenon, which we refer to as the facet-braiding effect, has been recognized in some previous publications, but to our knowledge its nature has never been analyzed. We propose a technique for attenuating the facet-braiding effect. We have conducted experiments to illustrate the consequences of the facet-braiding effect on three-dimensional integral images, and we show the usefulness of the proposed technique in eliminating this effect.

Facet (geometry)Integral imagingOpticsThree dimensional imagingbusiness.industryComputer scienceImage processingIterative reconstructionThree dimensional televisionbusinessAtomic and Molecular Physics and OpticsDisplay deviceOptics letters
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