Search results for "Neural Networks"

showing 10 items of 599 documents

Recognition of Human Actions Through Deep Neural Networks for Multimedia Systems Interaction

2019

Nowadays, interactive multimedia systems are part of everyday life. The most common way to interact and control these devices is through remote controls or some sort of touch panel. In recent years, due to the introduction of reliable low-cost Kinect-like sensing technology, more and more attention has been dedicated to touchless interfaces. A Kinect-like devices can be positioned on top of a multimedia system, detect a person in front of the system and process skeletal data, optionally with RGBd data, to determine user gestures. The gestures of the person can then be used to control, for example, a media device. Even though there is a lot of interest in this area, currently, no consumer sy…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniHuman machine interaction;gesture recognitionneural networksMultimedia system interaction
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Mathematical Patterns and Cognitive Architectures

2014

Mathematical patterns are an important subclass of the class of patterns. The main task of this paper is examining a particular proposal concerning the nature of mathematical patterns and some elements of the cognitive architecture an agent should have to recognize them.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionimathematical patterns neural networks conceptual spaces systems of representationSettore M-FIL/02 - Logica E Filosofia Della Scienza
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Fake News Spreaders Detection: Sometimes Attention Is Not All You Need

2022

Guided by a corpus linguistics approach, in this article we present a comparative evaluation of State-of-the-Art (SotA) models, with a special focus on Transformers, to address the task of Fake News Spreaders (i.e., users that share Fake News) detection. First, we explore the reference multilingual dataset for the considered task, exploiting corpus linguistics techniques, such as chi-square test, keywords and Word Sketch. Second, we perform experiments on several models for Natural Language Processing. Third, we perform a comparative evaluation using the most recent Transformer-based models (RoBERTa, DistilBERT, BERT, XLNet, ELECTRA, Longformer) and other deep and non-deep SotA models (CNN,…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionitext classificationcorpus linguisticSettore ING-INF/03 - Telecomunicazionifake newTwitterauthor profilingconvolutional neural networkdeep learningNatural Language Processing (NLP)user classificationfake news; misinformation; Natural Language Processing (NLP); transformers; Twitter; convolutional neural networks; text classification; deep learning; machine learning; user classification; author profiling; corpus linguistics; linguistic analysismachine learningtransformermisinformationlinguistic analysisInformation Systems
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SHARP: Environment and Person Independent Activity Recognition with Commodity IEEE 802.11 Access Points

2022

In this article we present SHARP, an original approach for obtaining human activity recognition (HAR) through the use of commercial IEEE 802.11 (Wi-Fi) devices. SHARP grants the possibility to discern the activities of different persons, across different time-spans and environments. To achieve this, we devise a new technique to clean and process the channel frequency response (CFR) phase of the Wi-Fi channel, obtaining an estimate of the Doppler shift at a radio monitor device. The Doppler shift reveals the presence of moving scatterers in the environment, while not being affected by (environment-specific) static objects. SHARP is trained on data collected as a person performs seven differe…

Signal Processing (eess.SP)Networking and Internet Architecture (cs.NI)FOS: Computer and information scienceshuman activity recognitionMobile computingComputer Science - Machine LearningCFRMonitoringSensorsComputer Networks and CommunicationsIEEE 802.11acneural networksWi-Fi sensingMachine Learning (cs.LG)Computer Science - Networking and Internet ArchitectureCSIActivity recognitionFOS: Electrical engineering electronic engineering information engineeringPerformance evaluationFeature extractionWireless fidelityElectrical and Electronic EngineeringElectrical Engineering and Systems Science - Signal Processingcontactless indoor monitoringSoftware
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Structural and dynamical properties of sodium silicate melts: An investigation by molecular dynamics computer simulation

2001

We present the results of large scale computer simulations in which we investigate the static and dynamic properties of sodium disilicate and sodium trisilicate melts. We study in detail the static properties of these systems, namely the coordination numbers, the temperature dependence of the Q^(n) species and the static structure factor, and compare them with experiments. We show that the structure is described by a partially destroyed tetrahedral SiO_4 network and the homogeneously distributed sodium atoms which are surrounded on average by 16 silicon and other sodium atoms as nearest neighbors. We compare the diffusion of the ions in the sodium silicate systems with that in pure silica a…

SiliconStatistical Mechanics (cond-mat.stat-mech)Coordination numberSodiumDiffusionInorganic chemistrychemistry.chemical_elementFOS: Physical sciencesGeologySodium silicateDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksMolecular dynamicschemistry.chemical_compoundchemistryGeochemistry and PetrologyChemical physicsAtomPhysics::Atomic and Molecular ClustersStructure factorCondensed Matter - Statistical Mechanics
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Anam-Net: Anamorphic Depth Embedding-Based Lightweight CNN for Segmentation of Anomalies in COVID-19 Chest CT Images.

2021

Chest computed tomography (CT) imaging has become indispensable for staging and managing coronavirus disease 2019 (COVID-19), and current evaluation of anomalies/abnormalities associated with COVID-19 has been performed majorly by the visual score. The development of automated methods for quantifying COVID-19 abnormalities in these CT images is invaluable to clinicians. The hallmark of COVID-19 in chest CT images is the presence of ground-glass opacities in the lung region, which are tedious to segment manually. We propose anamorphic depth embedding-based lightweight CNN, called Anam-Net, to segment anomalies in COVID-19 chest CT images. The proposed Anam-Net has 7.8 times fewer parameters …

Similarity (geometry)Coronavirus disease 2019 (COVID-19)Computer Networks and CommunicationsComputer scienceComputed tomography02 engineering and technologyDeep LearningArtificial Intelligence0202 electrical engineering electronic engineering information engineeringMedical imagingmedicineImage Processing Computer-AssistedHumansSegmentationComputer visionLung regionLungmedicine.diagnostic_testbusiness.industryDeep learningVDP::Technology: 500COVID-19Image segmentationComputer Science ApplicationsEmbedding020201 artificial intelligence & image processingArtificial intelligenceNeural Networks ComputerbusinessTomography X-Ray ComputedSoftwareIEEE transactions on neural networks and learning systems
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The reliability and validity of the sport engagement instrument in the Finnish dual career context

2021

Although engagement is key to predicting burnout and dropout, few existing instruments measure this phenomenon in the sports context. As part of a larger three-year Lower Secondary Sports Schools Pilot Project (LSSSPP) in Finland, we conducted two studies as part of the present research with the major aims of (a) constructing the Sport Engagement Instrument (SpEI) and (b) validating the new instrument in the Finnish dual career context. In the preparatory study, an expert panel constructed the SpEI, a questionnaire comprising 37 items intended to measure cognitive and affective sports engagement. The main study utilised questionnaire data collected from two independent samples (n1 = 992 and…

Social PsychologyCognitive engagementquestionnaireApplied psychologykyselytutkimuscognitive engagementContext (language use)sitoutuminenBurnoutbehavioural engagementuupumusDual (category theory)urheilu-uranuoretaffective engagementvaliditeettiPhenomenonopiskeluPsychologyApplied PsychologyDropout (neural networks)Reliability (statistics)reliabiliteettiInternational Journal of Sport and Exercise Psychology
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Disordered and Frustrated Spin Systems

2007

A brief review on the effects of quenched disorder on magnetic ordering is given. This disorder can be due to dilution of a ferro- or antiferromagnetic crystal with nonmagnetic atoms, or due to noncrystallinity (amorphous magnetic systems). This disorder in the positions of the magnetic atoms leads to disorder in the exchange interactions between spins. If the disorder is sufficiently weak, the critical temperature of magnetic ordering is somewhat decreased, and the critical behavior may change, but the nature of ordering is maintained. However, if the disorder is sufficiently strong, magnetic long-range order may disappear altogether at a percolation threshold, or a new type of order may a…

Spin glassMaterials scienceCondensed matter physicsSpinsmedia_common.quotation_subjectGeometrical frustrationFrustrationPercolation thresholdCondensed Matter::Disordered Systems and Neural NetworksFerromagnetismOrder and disorderAntiferromagnetismCondensed Matter::Strongly Correlated Electronsmedia_common
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The manifestation of dipoles clustering in paraelectric phase of disordered ferroelectrics

2001

Abstract We predict the existence of Griffiths phase in the dielectrics with concentrational crossover between dipole glass (electric analog of spin glass) and ferroelectricity. The peculiar representatives of above substances are KTaO3: Li, Nb, Na or relaxor ferroelectrics like Pb1−xLaxZr0.65Ti0.35O3. Since this phase exists above ferroelectric phase transition temperature (but below that temperature for ordered substance), we call it “para-glass phase”. We assert that the difference between paraelectric and para-glass phase of above substances is the existence of clusters (inherent to “ordinary” Griffiths phase in Ising magnets) of correlated dipoles. We show that randomness play a decisi…

Spin glassMaterials scienceCondensed matter physicsTransition temperatureCondensed Matter PhysicsCondensed Matter::Disordered Systems and Neural NetworksFerroelectricityElectronic Optical and Magnetic MaterialsCondensed Matter::Materials ScienceElectric dipole momentDipoleMean field theoryPhase (matter)Ising modelFerroelectrics
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Performance potential for simulating spin models on GPU

2012

Graphics processing units (GPUs) are recently being used to an increasing degree for general computational purposes. This development is motivated by their theoretical peak performance, which significantly exceeds that of broadly available CPUs. For practical purposes, however, it is far from clear how much of this theoretical performance can be realized in actual scientific applications. As is discussed here for the case of studying classical spin models of statistical mechanics by Monte Carlo simulations, only an explicit tailoring of the involved algorithms to the specific architecture under consideration allows to harvest the computational power of GPU systems. A number of examples, ran…

Spin glassPhysics and Astronomy (miscellaneous)Computer scienceMonte Carlo methodFOS: Physical sciencesComputational scienceCUDAHigh Energy Physics - LatticeStatistical physicsGraphicsCondensed Matter - Statistical MechanicsNumerical AnalysisStatistical Mechanics (cond-mat.stat-mech)Applied MathematicsHigh Energy Physics - Lattice (hep-lat)RangingStatistical mechanicsDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksComputational Physics (physics.comp-ph)Computer Science ApplicationsComputational MathematicsModeling and SimulationIsing modelParallel temperingPhysics - Computational Physics
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