Search results for "machine learning"

showing 10 items of 1464 documents

A Navigation and Augmented Reality System for Visually Impaired People

2021

In recent years, we have assisted with an impressive advance in augmented reality systems and computer vision algorithms, based on image processing and artificial intelligence. Thanks to these technologies, mainstream smartphones are able to estimate their own motion in 3D space with high accuracy. In this paper, we exploit such technologies to support the autonomous mobility of people with visual disabilities, identifying pre-defined virtual paths and providing context information, reducing the distance between the digital and real worlds. In particular, we present ARIANNA+, an extension of ARIANNA, a system explicitly designed for visually impaired people for indoor and outdoor localizati…

navigation; visually impaired; computer vision; augmented reality; cultural context; convolutional neural network; machine learning; hapticExploitComputer scienceconvolutional neural networkImage processingContext (language use)02 engineering and technologyTP1-1185BiochemistryConvolutional neural networkArticleMotion (physics)computer visionAnalytical ChemistrySettore ING-INF/04 - AutomaticaArtificial IntelligenceHuman–computer interactioncultural context0202 electrical engineering electronic engineering information engineeringHumansElectrical and Electronic EngineeringnavigationInstrumentationHaptic technologySettore ING-INF/03 - TelecomunicazioniChemical technology020206 networking & telecommunicationsAtomic and Molecular Physics and Opticsaugmented realitymachine learning020201 artificial intelligence & image processingAugmented realityvisually impairedNeural Networks ComputerhapticAlgorithmsVisually Impaired PersonsPATH (variable)augmented reality computer vision convolutional neural network cultural context haptic machine learning navigation visually impaired Algorithms Artificial Intelligence Humans Neural Networks Computer Augmented Reality Visually Impaired PersonsSensors
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Hyper-flexible Convolutional Neural Networks based on Generalized Lehmer and Power Means

2022

Convolutional Neural Network is one of the famous members of the deep learning family of neural network architectures, which is used for many purposes, including image classification. In spite of the wide adoption, such networks are known to be highly tuned to the training data (samples representing a particular problem), and they are poorly reusable to address new problems. One way to change this would be, in addition to trainable weights, to apply trainable parameters of the mathematical functions, which simulate various neural computations within such networks. In this way, we may distinguish between the narrowly focused task-specific parameters (weights) and more generic capability-spec…

neural networkCognitive NeuroscienceLehmer meansyväoppiminenneuroverkotMachine LearningflexibilitykoneoppiminenPower meanArtificial Intelligenceconvolutionadversarial robustnesspoolingNeural Networks Computeractivation functionconvolutionalgeneralization
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Course Satisfaction in Engineering Education Through the Lens of Student Agency Analytics

2020

This Research Full Paper presents an examination of the relationships between course satisfaction and student agency resources in engineering education. Satisfaction experienced in learning is known to benefit the students in many ways. However, the varying significance of the different factors of course satisfaction is not entirely clear. We used a validated questionnaire instrument, exploratory statistics, and supervised machine learning to examine how the different factors of student agency affect course satisfaction among engineering students (N = 293). Teacher’s support and trust for the teacher were identified as both important and critical factors concerning experienced course satisf…

opintomenestystekniset alatAffect (psychology)Course satisfactionAgency (sociology)ComputingMilieux_COMPUTERSANDEDUCATIONsupervised machine learningopintotoimistotMedical educationopiskelijatbusiness.industryexploratory statistics05 social sciencesCritical factorscourse satisfaction050301 educationInformation technologyCitizen journalismkoneoppiminenEngineering educationAnalyticstyytyväisyysopiskelustudent agency0509 other social sciences050904 information & library sciencesbusinessPsychology0503 education
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Surrogate-assisted multicriteria optimization: Complexities, prospective solutions, and business case

2017

Complexity in solving real-world multicriteria optimization problems often stems from the fact that complex, expensive, and/or time-consuming simulation tools or physical experiments are used to evaluate solutions to a problem. In such settings, it is common to use efficient computational models, often known as surrogates or metamodels, to approximate the outcome (objective or constraint function value) of a simulation or physical experiment. The presence of multiple objective functions poses an additional layer of complexity for surrogate-assisted optimization. For example, complexities may relate to the appropriate selection of metamodels for the individual objective functions, extensive …

optimization problemsMathematical optimizationComputer scienceStrategy and Managementmedia_common.quotation_subjectConstraint (computer-aided design)0211 other engineering and technologiesmultiple criteria decision makingGeneral Decision Sciences02 engineering and technologyMulti-objective optimizationOutcome (game theory)evolutionary multicriteria optimizationEngineering optimizationmulticriteria optimization0202 electrical engineering electronic engineering information engineeringPoint (geometry)Business caseFunction (engineering)media_commonta113Computational model021103 operations researchmetamodelsexpensive optimization problemssurrogatesexpensesmachine learning020201 artificial intelligence & image processing
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Practices and Infrastructures for Machine Learning Systems : An Interview Study in Finnish Organizations

2022

Using interviews, we investigated the practices and toolchains for machine learning (ML)-enabled systems from 16 organizations across various domains in Finland. We observed some well-established artificial intelligence engineering approaches, but practices and tools are still needed for the testing and monitoring of ML-enabled systems. Peer reviewed

organizationscomputational modelingliiketoimintaprosessitGeneral Computer Scienceinterviewsbusiness practicesohjelmistotuotantoorganisaatiotmonitorointitekoäly113 Computer and information sciencesartificial intelligencelearning systemsdata modelsmonitoringmachine learningkoneoppiminenälytekniikkahaastattelututkimussoftware engineering
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Limiting Carleman weights and conformally transversally anisotropic manifolds

2020

We analyze the structure of the set of limiting Carleman weights in all conformally flat manifolds, 3 3 -manifolds, and 4 4 -manifolds. In particular we give a new proof of the classification of Euclidean limiting Carleman weights, and show that there are only three basic such weights up to the action of the conformal group. In dimension three we show that if the manifold is not conformally flat, there could be one or two limiting Carleman weights. We also characterize the metrics that have more than one limiting Carleman weight. In dimension four we obtain a complete spectrum of examples according to the structure of the Weyl tensor. In particular, we construct unimodular Lie groups whose …

osittaisdifferentiaaliyhtälötComputer Science::Machine LearningApplied MathematicsGeneral Mathematics010102 general mathematicsMathematical analysis35R30 53A30LimitingMathematics::Spectral TheoryComputer Science::Digital Libraries01 natural sciencesinversio-ongelmatdifferentiaaligeometria010101 applied mathematicsStatistics::Machine LearningMathematics - Analysis of PDEsFOS: MathematicsComputer Science::Mathematical Softwaremonistot0101 mathematicsAnisotropyAnalysis of PDEs (math.AP)MathematicsTransactions of the American Mathematical Society
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Emotions and Activity Recognition System Using Wearable Device Sensors

2021

Nowadays machines have become extremely smart, there are a lot of existing services that seemed to be unexpectable and futuristic decades or even a few years ago. However, artificial intelligence is still far from human intelligence, machines do not have feelings, consciousness, and intuition. How can we help machines to learn about human feelings and understand their needs better? People take their devices wherever they go, what can devices tell us about their owners? Personal preferences and needs are dependent on emotional and situational contexts. Therefore, emotional and activity aware gadgets would be more intuitive and provide more appropriate information to users. Contemporary weara…

paikkatiedotComputer sciencemedia_common.quotation_subjectWearable computertekoälyRecommender systemwearable device sensorslcsh:TelecommunicationActivity recognitiontoimintatunteetHuman–computer interactionlcsh:TK5101-6720emotions recognitionzero-shot semantic segmentationactivity recognitionanturitSituational ethicsimage segmentationWearable technologymedia_commonHuman intelligencebusiness.industrymielialadeep learningliikkeentunnistusmachine learningkoneoppiminenälytuotteetFeelingälytekniikkaConsciousnessbusinesskasvontunnistus (tietotekniikka)fyysinen aktiivisuus2021 28th Conference of Open Innovations Association (FRUCT)
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El tratamiento personalizado de la insuficiencia velofaríngea mediante injerto adiposo autólogo de la faringe

2022

La incompetencia velofaríngea (IVP), definida por Lermoyez como un “desajuste anatómico y funcional entre el paladar blando y la faringe durante el habla”, es un problema funcional que requiere una gestión multidisciplinar con un estudio dinámico de las dos estructuras implicadas en el emisión de las palabras mediante la visión directa de los movimientos musculares durante la producción de fonemas. Varios estudios radiológicos han trabajado en la visualización dinámica del cierre velofaríngeo. Pigott fue el primero en introducir la nasofibroscopia en el estudio de la IVP. Ahora, el uso de la resonancia magnética funcional para el estudio del habla está en pleno desarrollo. Éste es un trabaj…

perfect speechinteligencia artificialcirugia pediatricafaringoplastialogopediaUNESCO::MATEMÁTICAS::Estadística ::Análisis de datosUNESCO::MATEMÁTICAS::Ciencia de los ordenadores::Inteligencia artificialUNESCO::CIENCIAS MÉDICAS ::Cirugía ::Otrasmachine learningpalabraUNESCO::LINGÜÍSTICA::Lingüística sincrónica::Fonologíaautoinjerto adiposoUNESCO::MATEMÁTICAS::Estadística ::Teoría y procesos de decisiónUNESCO::CIENCIAS MÉDICASUNESCO::MATEMÁTICAS::Estadística ::Técnicas de inferencia estadísticaUNESCO::CIENCIAS MÉDICAS ::Cirugía ::Cirugía de garganta nariz y oídosinsuficiencia velofaringeaUNESCO::MATEMÁTICAS::Estadística ::Análisis multivarianteotorrinolaringologia
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Evaluating the Efficiency of Different Regression, Decision Tree, and Bayesian Machine Learning Algorithms in Spatial Piping Erosion Susceptibility U…

2020

Piping erosion is one form of water erosion that leads to significant changes in the landscape and environmental degradation. In the present study, we evaluated piping erosion modeling in the Zarandieh watershed of Markazi province in Iran based on random forest (RF), support vector machine (SVM), and Bayesian generalized linear models (Bayesian GLM) machine learning algorithms. For this goal, due to the importance of various geo-environmental and soil properties in the evolution and creation of piping erosion, 18 variables were considered for modeling the piping erosion susceptibility in the Zarandieh watershed. A total of 152 points of piping erosion were recognized in the study area that…

pipinglcsh:Sdeep learninggeoinformaticshazard mappingnatural hazarderosionsusceptibilityBayesian generalized linear model (Bayesian GLM)lcsh:Agriculturemachine learningspatial modelinggeohazardbig datasupport vector machinedata sciencerandom forestLand
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Dataset related to article "Development and external validation of a clinical prediction model for functional impairment after intracranial tumor sur…

2021

Anonymised clinical database containing information (Age, sex, prior surgery, tumor histology and maximum diameter, expected major brain vessel or cranial nerve manipulation, resection in eloquent areas and the posterior fossa, and surgical approach were recorded) about patients of Fondazione IRCCS Istituto Besta analysed for the article “Development and external validation of a clinical prediction model for functional impairment after intracranial tumor surgery”

predictive analyticsmachine learningfunctional impairmentoncologyneurosurgeryoutcome prediction
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