Search results for "Artificial"

showing 10 items of 7394 documents

Integration of multiple range and intensity image pairs using a volumetric method to create textured three-dimensional models

2001

We present a volumetric approach to three-dimensional (3D) object modeling that differs from previous techniques in that both object texture and geometry are considered in the reconstruc- tion process. The motivation for the research is the simulation of a thermal tire inspection station. Integrating 3D geometry information with two-dimensional thermal images permits the thermal informa- tion to be displayed as a texture map on the tire structure, enhanc- ing analysis capabilities. Additionally, constructing the tire geometry during the inspection process allows the tire to be examined for structural defects that might be missed if the thermal data were textured onto a predefined model. Exp…

business.industryMachine visionComputer scienceProcess (computing)Volume rendering3D modelingAtomic and Molecular Physics and OpticsComputer Science ApplicationsVisualizationComputer data storageObject modelComputer visionArtificial intelligenceElectrical and Electronic EngineeringbusinessTexture mappingJournal of Electronic Imaging
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Pattern image enhancement by extended depth of field

2014

Abstract Most optical defect localization techniques such as dynamic laser stimulation or photon emission microscopy require a pattern image of the device to be taken. The main purpose is for device navigation, but it also enables the analyst to identify the location of the monitored activity by superimposing it onto the pattern image. The defect localization workflow usually starts at low or medium magnification. At these scales, several factors can lead to a lack of orthogonality of the sample with the optical axis of the system. Therefore, images can be locally out of focus and poorly resolved. In this paper, a method based on Depth of Field Extension is suggested to correct the pattern …

business.industryMagnificationImage processingCondensed Matter PhysicsLaserAtomic and Molecular Physics and OpticsSurfaces Coatings and FilmsElectronic Optical and Magnetic Materialslaw.inventionFocus stackingOptical axisOpticslawComputer visionDepth of fieldArtificial intelligenceElectrical and Electronic EngineeringSafety Risk Reliability and QualitybusinessFocus (optics)Infrared microscopyMathematicsMicroelectronics Reliability
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Validation of a Reinforcement Learning Policy for Dosage Optimization of Erythropoietin

2007

This paper deals with the validation of a Reinforcement Learning (RL) policy for dosage optimization of Erythropoietin (EPO). This policy was obtained using data from patients in a haemodialysis program during the year 2005. The goal of this policy was to maintain patients' Haemoglobin (Hb) level between 11.5 g/dl and 12.5 g/dl. An individual management was needed, as each patient usually presents a different response to the treatment. RL provides an attractive and satisfactory solution, showing that a policy based on RL would be much more successful in achieving the goal of maintaining patients within the desired target of Hb than the policy followed by the hospital so far. In this work, t…

business.industryManagement scienceComputer scienceMachine learningcomputer.software_genreData setWork (electrical)Robustness (computer science)ErythropoietinmedicineReinforcement learningArtificial intelligencebusinesscomputermedicine.drug
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Real And Positive Filter Based On Circular Harmonic Expansion

1989

A real and positive filter for pattern recognition is presented. The filter, based on the circular harmonic (CH) expansion of a real function, is partially rotation invariant. As it is real and positive, the filter can be recorded on a transparency as an amplitude filter. Computer simulations of character recognition show a partial rotation invariance of about 40°. Optical experiments agree with these results and with acceptable discrimination between different characters. Nevertheless, due to experimental difficulties, the method is onerous for use in general pattern recognition problems.

business.industryMathematical analysisReal-valued functionFilter (video)Optical correlatorPattern recognition (psychology)HarmonicComputer visionArtificial intelligenceOptical filterbusinessRotation (mathematics)Linear filterMathematicsSPIE Proceedings
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Perceptually weighted optical flow for motion-based segmentation in MPEG-4 paradigm

2000

In the MPEG-4 paradigm, the sequence must be described in terms of meaningful objects. This meaningful, high-level representation should emerge from low-level primitives such as optical flow and prediction error which are the basic elements of previous-generation video coders. The accuracy of the high-level models strongly depends on the robustness of the primitives used. It is shown how perceptual weighting in optical flow computation gives rise to better motion estimates which consistently improve motion-based segmentation compared to equivalent unweighted motion estimates.

business.industryMean squared prediction errorComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONOptical flowcomputer.file_formatPerceptual weightingOptical flow computationRobustness (computer science)Motion estimationComputer Science::MultimediaMPEG-4Computer visionSegmentationArtificial intelligenceElectrical and Electronic EngineeringbusinesscomputerMathematicsElectronics Letters
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Development of a multispectral imagery device devoted to weed detection

2003

Multispectral imagery is a large domain with number of practical applications: thermography, quality control in industry, food science and agronomy, etc. The main interest is to obtain spectral information of the objects for which reflectance signal can be associated with physical, chemical and/or biological properties. Agronomic applications of multispectral imagery generally involve the acquisition of several images in the wavelengths of visible and near infrared. This paper will first present different kind of multispectral devices used for agronomic issues and will secondly introduce an original multispectral design based on a single CCD. Third, early results obtained for weed detection…

business.industryMultispectral imageWeed detectionReflectivityMultispectral pattern recognitionGeographyBiological propertyThermographyComputer visionArtificial intelligencebusinessOptical filterImage resolutionRemote sensingSPIE Proceedings
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View Planning Approach for Automatic 3D Digitization of Unknown Objects

2012

International audience; This paper addresses the view planning problem for the digitization of 3D objects without prior knowledge on their shape and presents a novel surface approach for the Next Best View (NBV) computation. The proposed method uses the concept of Mass Vector Chains (MVC) to define the global orientation of the scanned part. All of the viewpoints satisfying an orientation constraint are clustered using the Mean Shift technique to construct a first set of candidates for the NBV. Then, a weight is assigned to each mode according to the elementary orientations of its different descriptors. The NBV is chosen among the modes with the highest weights and which comply with the rob…

business.industryOrientation (computer vision)Computer science[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]02 engineering and technology[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Constraint (information theory)Set (abstract data type)[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020204 information systems0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer visionArtificial intelligenceMean-shiftbusinessDigitization
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Towards interpretable classifiers with blind signal separation

2012

Blind signal separation (BSS) is a powerful tool to open-up complex signals into component sources that are often interpretable. However, BSS methods are generally unsupervised, therefore the assignment of class membership from the elements of the mixing matrix may be sub-optimal. This paper proposes a three-stage approach using Fisher information metric to define a natural metric for the data, from which a Euclidean approximation can then be used to drive BSS. Results with synthetic data models of real-world high-dimensional data show that the classification accuracy of the method is good for challenging problems, while retaining interpretability.

business.industryPattern recognitionBlind signal separationSynthetic dataData mappingsymbols.namesakeComponent (UML)Metric (mathematics)symbolsArtificial intelligenceFisher informationbusinessFisher information metricInterpretabilityMathematics
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PD recognition by means of statistical and fractal parameters and a neural network

2000

A novel partial discharge (PD) defect identification method is described. Starting with PD data on different families of specimens, a suitable set of parameters are determined and then used as input variables to a neural network for the purpose of identifying the defects within the insulation. In this procedure the statistical Weibull analysis is performed on PD pulse amplitude histograms to obtain the scale parameter /spl alpha/ and the shape parameter /spl beta/. Thereafter, the two statistical operators (skewness and kurtosis) and two fractal parameters (fractal dimension and lacunarity) are evaluated from the PD phase on the discharge epoch histogram and from the 3 dimensional (pulse am…

business.industryPattern recognitionFractal dimensionShape parameterFractalHistogramLacunarityPartial dischargeKurtosisArtificial intelligenceElectrical and Electronic EngineeringbusinessScale parameterMathematicsIEEE Transactions on Dielectrics and Electrical Insulation
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Unsupervised clustering method for pattern recognition in IIF images

2017

Autoimmune diseases are a family of more than 80 chronic, and often disabling, illnesses that develop when underlying defects in the immune system lead the body to attack its own organs, tissues, and cells. Diagnosis of autoimmune pathologies is based on research and identification of antinuclear antibodies (ANA) through indirect immunofluorescence (IIF) method and is performed by analyzing patterns and fluorescence intensity. We propose here a method to automatically classify the centromere pattern based on the grouping of centromeres on the cells through a clustering K-means algorithm. The described method was tested on a public database (MIVIA). The results of the test showed an Accuracy…

business.industryPattern recognitionIIfBiologyIIF imageSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)K-meanIdentification (information)Fluorescence intensityStatistical classificationPattern recognitionPattern recognition (psychology)Autoimmune diseaseAutomatic segmentationArtificial intelligenceUnsupervised clusteringCluster analysisbusinessclustering
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