Search results for "computer.software_genre"

showing 10 items of 3858 documents

Context-sensitive distraction warnings : effects on drivers' visual behavior and acceptance

2016

In this study, we investigated the effects of context-sensitive distraction warnings on drivers' in-car glance behaviors and acceptance. The studied prototype warning application functions on a smart phone. The novelty of the application is its proactive and context-sensitive approach to the adjustment of warning thresholds according to the estimated visual demands of the driving situation ahead. In our study, novice and experienced drivers conducted in-car tasks with a smart phone on a test track with and without the warnings. The application gave a warning if the driver's gaze was recognized to remain on the smart phone over a situation-specific threshold time, or if the driver was approa…

driver distractionSituation awarenessComputer sciencehyväksyminen (menettely)Applied psychologywarning systemHuman Factors and ErgonomicsContext (language use)Computer securitycomputer.software_genreEducationTask (project management)Distraction0502 economics and business0501 psychology and cognitive sciencessmart phone050107 human factorsta113050210 logistics & transportationta213Warning system05 social sciencesGeneral EngineeringtrustGazeHuman-Computer InteractionHardware and Architecturesituation awarenessluottamuscomputerSoftwareacceptance
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The role of expert evaluation for microsleep detection

2015

Abstract Recently, it has been shown by overnight driving simulation studies that microsleep density is the only known sleepiness indicator which rapidly increases within a few seconds immediately before sleepiness related crashes. This indicator is based solely on EEG and EOG and subsequent adaptive pattern recognition. Accurate microsleep recognition is very important for the performance of this sleepiness indicator. The question is whether expensive evaluations of microsleep events by a) experts are necessary or b) non-experts provide sufficient evaluations. Based on 11,114 microsleep events in case a) and 12,787 in case b) recognition accuracies were investigated utilizing (i) artificia…

driving simulationmicrosleepMicrosleepArtificial neural networkmedicine.diagnostic_testComputer sciencebusiness.industryBiomedical EngineeringRElectroencephalographysupport-vector machinesMachine learningcomputer.software_genresleepinessneural networksSupport vector machineeogExpert evaluationmedicineDriving simulationMedicineArtificial intelligenceeegbusinesscomputerCurrent Directions in Biomedical Engineering
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VEBO: Validation of E-R diagrams through ontologies and WordNet

2012

In the semantic web vision, ontologies are building blocks for providing applications with a high level description of the operating environment in support of interoperability and semantic capabilities. The importance of ontologies in this respect is clearly stated in many works. Another crucial issue to increase the semantic aspect of web is to enrich the level of expressivity of database related data. Nowadays, databases are the primary source of information for dynamical web sites. The linguistic data used to build the database structure could be relevant for extracting meaningful information. In most cases, this type of information is not used for information retrieval. The work present…

e-r DiagramInformation retrievalbusiness.industryRelational databaseComputer scienceOntologyInteroperabilityWord processingWordNetOntology (information science)computer.software_genreSemanticsRule-based machine translationArtificial intelligencebusinesscomputerSemantic WebNatural language processing
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Natural induction: An objective bayesian approach

2009

The statistical analysis of a sample taken from a finite population is a classic problem for which no generally accepted objective Bayesian results seem to exist. Bayesian solutions to this problem may be very sensitive to the choice of the prior, and there is no consensus as to the appropriate prior to use.

education.field_of_studyAlgebra and Number Theorybusiness.industryApplied MathematicsBayesian probabilityPopulationBayes factorSample (statistics)Machine learningcomputer.software_genreBinomial distributionBayesian statisticsComputational MathematicsEconometricsBayesian hierarchical modelingGeometry and TopologyArtificial intelligencebusinesseducationcomputerAnalysisJeffreys priorMathematicsRevista de la Real Academia de Ciencias Exactas, Fisicas y Naturales. Serie A. Matematicas
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Principal Component and Neural Network Analyses of Face Images: What Can Be Generalized in Gender Classification?

1998

We present an overview of the major findings of the principal component analysis (pca) approach to facial analysis. In a neural network or connectionist framework, this approach is known as the linear autoassociator approach. Faces are represented as a weighted sum of macrofeatures (eigenvectors or eigenfaces) extracted from a cross-product matrix of face images. Using gender categorization as an illustration, we analyze the robustness of this type of facial representation. We show that eigenvectors representing general categorical information can be estimated using a very small set of faces and that the information they convey is generalizable to new faces of the same population and to a l…

education.field_of_studyArtificial neural networkbusiness.industryApplied MathematicsPopulationPattern recognitionMachine learningcomputer.software_genreComputingMethodologies_PATTERNRECOGNITIONEigenfaceCategorizationRobustness (computer science)Face (geometry)Principal component analysisArtificial intelligencebusinesseducationcomputerCategorical variableGeneral PsychologyMathematicsJournal of Mathematical Psychology
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DAE-GP

2020

Estimation of distribution genetic programming (EDA-GP) algorithms are metaheuristics where sampling new solutions from a learned probabilistic model replaces the standard mutation and recombination operators of genetic programming (GP). This paper presents DAE-GP, a new EDA-GP which uses denoising autoencoder long short-term memory networks (DAE-LSTMs) as probabilistic model. DAE-LSTMs are artificial neural networks that first learn the properties of a parent population by mapping promising candidate solutions to a latent space and reconstructing the candidate solutions from the latent space. The trained model is then used to sample new offspring solutions. We show on a generalization of t…

education.field_of_studyArtificial neural networkbusiness.industryComputer scienceOffspringPopulationProbabilistic logicGenetic programmingStatistical model0102 computer and information sciences02 engineering and technologyMachine learningcomputer.software_genre01 natural sciencesTree (data structure)Estimation of distribution algorithm010201 computation theory & mathematics0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingArtificial intelligencebusinesseducationcomputerMetaheuristicProceedings of the 2020 Genetic and Evolutionary Computation Conference
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Atlas construction and image analysis using statistical cardiac models

2010

International audience; This paper presents a brief overview of current trends in the construction of population and multi-modal heart atlases in our group and their application to atlas-based cardiac image analysis. The technical challenges around the construction of these atlases are organized around two main axes: groupwise image registration of anatomical, motion and fiber images and construction of statistical shape models. Application-wise, this paper focuses on the extraction of atlas-based biomarkers for the detection of local shape or motion abnormalities, addressing several cardiac applications where the extracted information is used to study and grade different pathologies. The p…

education.field_of_studyAtlas (topology)Computer sciencebusiness.industryPopulationImage registration02 engineering and technologycomputer.software_genreIndependent component analysisMotion (physics)030218 nuclear medicine & medical imagingImage (mathematics)03 medical and health sciences0302 clinical medicine0202 electrical engineering electronic engineering information engineeringMyocardial motion[INFO.INFO-IM]Computer Science [cs]/Medical Imaging020201 artificial intelligence & image processingComputer visionData miningArtificial intelligenceeducationbusinesscomputer
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Scatter Search for the Point-Matching Problem in 3D Image Registration

2008

Scatter search is a population-based method that has recently been shown to yield promising outcomes for solving combinatorial and nonlinear optimization problems. Based on formulations originally proposed in the 1960s for combining decision rules and problem constraints, such as the surrogate constraint method, scatter search uses strategies for combining solution vectors that have proved effective in a variety of problem settings. We present a scatter-search implementation designed to find high-quality solutions for the 3D image-registration problem, which has many practical applications. This problem arises in computer vision applications when finding a correspondence or transformation …

education.field_of_studyComputer scienceHeuristic (computer science)business.industryPopulationComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONGeneral EngineeringImage registrationPoint set registrationMachine learningcomputer.software_genreEvolutionary computationNonlinear programmingRobustness (computer science)Artificial intelligenceeducationbusinessMetaheuristicAlgorithmcomputerINFORMS Journal on Computing
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Modeling of female human body shapes for apparel design based on cross mean sets

2014

This paper is concerned with a method to build prototypes of human bodies that can be used for apparel design. One of the most important issues in the apparel development process is to define a sizing system to provide a good fitting for the majority of the population. Since anthropometric measures do not present the same linear growth with size in each dimension, it is very important to find a prototype that represents as accurately as possible each class in the sizing system. In this paper we propose a method based on the concept of random compact mean set to define prototypes in apparel design. From a cloud of 3D points obtained with a 3D scanner a solid that represents the human body is…

education.field_of_studyComputer sciencePopulationGeneral EngineeringClass (philosophy)Sample (statistics)Mean setsHuman bodies prototypescomputer.software_genre3D shapeSizingComputer Science ApplicationsSet (abstract data type)Artificial IntelligenceData miningDimension (data warehouse)educationcomputerRandom compact setsSimulationRealization (probability)Expert Systems with Applications
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Bayesian Hierarchical Models for Random Routes in Finite Populations

1996

In many practical situations involving sampling from finite populations, it is not possible (or it is prohibitely expensive) to access, or to even produce, a listing of all of the units in the population. In these situations, inferences can not be based on random samples from the population. Random routes are widely used procedures to collect data in absence of well defined sampling frames, and they usually have either been improperly analyzed as random samples, or entirely ignored as useless. We present here a Bayesian analysis of random routes that incorporates the information provided but carefully takes into account the non- randomness in the selection of the units.

education.field_of_studyComputer sciencePosterior probabilityPopulationBayesian probabilitySampling (statistics)Conditional probability distributioncomputer.software_genresymbols.namesakesymbolsData miningeducationcomputerSelection (genetic algorithm)RandomnessGibbs sampling
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