Search results for "NEURAL NETWORK"

showing 10 items of 1385 documents

Wind speed spatial estimation for energy planning in Sicily: introduction and statistical analysis

2008

Abstract The exploitation of the renewable energy sources plays a key role for achieving the CO 2 emissions reduction targets established by the Kyoto Protocol, as well as for facing the shortage of world fossil fuels reserves. In countries like Italy, with an high potential in terms of wind power generation, an efficient energy planning based on renewables is a very complex task. It encompasses many aspects: the resource availability assessment, the compliance with environmental and legislative constraints and last, but not least, the technical aspects linked to the safe integration to the grid of the intermittent power generated by the wind farms. This paper is the first part of a study a…

Wind powerSettore ING-IND/11 - Fisica Tecnica AmbientaleMeteorologyRenewable Energy Sustainability and the Environmentbusiness.industryWindEnergy planningWind speedNeural networkRenewable energyKrigingKrigingIDWEnvironmental scienceSpatial variabilityWeibullbusinessSicilyEfficient energy useWeibull distribution
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Wittgenstein, Turing, and Neural Networks

2018

The main task of this paper is grounding the socio-anthropological “naturalization” of meaning operated by the later Wittgenstein in his remarks on rule-following in the Philosophical Investigations in considerations relating to models of low-level (biological) processes of imitation, training, and learning. If the operation suggested above is successful, two of its immediate consequences are that the social aspect of language can no longer be considered as a primitive notion, but needs to be placed upon, if not reduced to, a biological foundation; and that the study of thought, and, actually, of certain brain processes, becomes prior in the order of explanation to the study of language. Th…

Wittgenstein Turing Neural Networks Cognitive Science Artificial Intelligence Naturalism learning trainingSettore M-FIL/02 - Logica E Filosofia Della Scienza
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Forecasting the Cell Temperature of PV Modules with an Adaptive System

2013

The need to reduce energy consumptions and to optimize the processes of energy production has pushed the technology towards the implementation of hybrid systems for combined production of electric and thermal energy. In particular, recent researches look with interest at the installation of hybrid system PV/T. To improve the energy performance of these systems, it is necessary to know the operating temperature of the photovoltaic modules. Furthermore, when photovoltaic (PV) systems replace the traditional building envelope materials and they are fully integrated (building integrated photovoltaic (BIPV)), it is very important to correctly assess their thermal behaviour. The determination of …

Work (thermodynamics)Settore ING-IND/11 - Fisica Tecnica AmbientaleArtificial neural networkArticle SubjectRenewable Energy Sustainability and the EnvironmentComputer sciencePhotovoltaic systemlcsh:TJ807-830lcsh:Renewable energy sourcesGeneral Chemistryrenewable energyAtomic and Molecular Physics and OpticsReliability engineeringOperating temperatureHybrid systemAdaptive systemProduction (economics)General Materials Sciencepv modulenumerical modelEnergy (signal processing)artificial neural networkInternational Journal of Photoenergy
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Effect of disorder on Majorana localization in topological superconductors: a quasiclassical approach

2020

Two-dimensional (2D) topological superconductors (TS) host chiral Majorana modes (MMs) localized at the boundaries. In this work, we study the effect of disorder on the localization length of MMs in two-dimensional spin-orbit (SO) coupled superconductors within quasiclassical approximation. We find nonmonotonic behavior of the Majorana localization length as a function of disorder strength. At weak disorder, the Majorana localization length decreases with an increasing disorder strength. Decreasing the disorder scattering time below a crossover value ${\ensuremath{\tau}}_{c}$, the Majorana localization length starts to increase. The crossover scattering time depends on the relative magnitud…

Work (thermodynamics)suprajohtavuusField (physics)CrossoverFOS: Physical sciencessuperconductorsTopology01 natural sciencessuprajohteet010305 fluids & plasmasSuperconductivity (cond-mat.supr-con)disordered systems0103 physical sciencesMesoscale and Nanoscale Physics (cond-mat.mes-hall)010306 general physicsSuperconductivityPhysicsCondensed Matter - Mesoscale and Nanoscale Physicsmajorana fermionsScatteringCondensed Matter - SuperconductivityFunction (mathematics)Disordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksCoupling (probability)kvasihiukkasetMAJORANA
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Writer identification for historical handwritten documents using a single feature extraction method

2020

International audience; With the growth of artificial intelligence techniques the problem of writer identification from historical documents has gained increased interest. It consists on knowing the identity of writers of these documents. This paper introduces our baseline system for writer identification, tested on a large dataset of latin historical manuscripts used in the ICDAR 2019 competition. The proposed system yielded the best results using Scale Invariant Feature Transform (SIFT) as a single feature extraction method, without any preprocessing stage. The system was compared against four teams who participated in the competition with different feature extraction methods: SRS-LBP, SI…

Writer identificationComputer sciencebusiness.industryFeature extractionhistorical documentsScale-invariant feature transform020207 software engineeringPattern recognition02 engineering and technologyartificial intelligenceConvolutional neural networkSupport vector machineIdentification (information)sift descriptors0202 electrical engineering electronic engineering information engineeringIdentity (object-oriented programming)Unsupervised learning020201 artificial intelligence & image processing[INFO]Computer Science [cs]Artificial intelligencebusiness
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A nonlinear oscillators network devoted to image processing

2004

A contrast enhancement and image inverting tool using a lattice of uncoupled nonlinear oscillators is proposed. We show theoretically and numerically that the gray scale picture contrast is strongly enhanced even if this one is initially very small. An image inversion can be also obtained in real time with the same Cellular Nonlinear Network (CNN) without reconfiguration of the network. A possible electronic implementation of this CNN is finally discussed.

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer science[ PHYS.COND.CM-DS-NN ] Physics [physics]/Condensed Matter [cond-mat]/Disordered Systems and Neural Networks [cond-mat.dis-nn]Image processing[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingCellular nonlinear networksTopology01 natural sciencesGrayscale010305 fluids & plasmasNonlinear oscillators[NLIN.NLIN-PS]Nonlinear Sciences [physics]/Pattern Formation and Solitons [nlin.PS][INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingControl theoryLattice (order)0103 physical sciences[ NLIN.NLIN-PS ] Nonlinear Sciences [physics]/Pattern Formation and Solitons [nlin.PS][PHYS.COND.CM-DS-NN]Physics [physics]/Condensed Matter [cond-mat]/Disordered Systems and Neural Networks [cond-mat.dis-nn]010306 general physicsEngineering (miscellaneous)ComputingMilieux_MISCELLANEOUSArtificial neural networkApplied MathematicsControl reconfigurationInversion (meteorology)neural networks[ SPI.TRON ] Engineering Sciences [physics]/Electronics[SPI.TRON]Engineering Sciences [physics]/ElectronicsNonlinear systemComputer Science::Computer Vision and Pattern RecognitionModeling and SimulationNonlinear dynamics[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Reconstruction of hyperspectral cutaneous data from an artificial neural network-based multispectral imaging system.

2011

International audience; The development of an integrated MultiSpectral Imaging (MSI) system yielding hyperspectral cubes by means of artificial neural networks is described. The MSI system is based on a CCD camera, a rotating wheel bearing a set of seven interference filters, a light source and a computer. The resulting device has been elaborated for in vivo imaging of skin lesions. It provides multispectral images and is coupled with a software reconstructing hyperspectral cubes from multispectral images. Reconstruction is performed by a neural network-based algorithm using heteroassociative memories. The resulting hyperspectral cube provides skin optical reflectance spectral data combined…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer scienceMultispectral imageHealth InformaticsDermoscopy[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing01 natural sciencesSensitivity and SpecificitySkin DiseasesMultispectral pattern recognition010309 opticsImaging systemSoftware[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingInterference (communication)0103 physical sciencesImage Interpretation Computer-AssistedSkin cancerHumansRadiology Nuclear Medicine and imagingComputer visionSpatial analysis[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingSpectral reflectanceRadiological and Ultrasound TechnologyArtificial neural networkbusiness.industryMultispectral images010401 analytical chemistryHyperspectral imagingReproducibility of ResultsEquipment DesignComputer Graphics and Computer-Aided Design0104 chemical sciencesEquipment Failure AnalysisHyperspectral cube reconstructionColorimetryComputer Vision and Pattern RecognitionArtificial intelligenceNeural Networks Computerbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingPreclinical imagingNeural networksFiltrationComputerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
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Kolmogorov Superposition Theorem and Its Application to Multivariate Function Decompositions and Image Representation

2008

International audience; In this paper, we present the problem of multivariate function decompositions into sums and compositions of monovariate functions. We recall that such a decomposition exists in the Kolmogorov's superposition theorem, and we present two of the most recent constructive algorithms of these monovariate functions. We first present the algorithm proposed by Sprecher, then the algorithm proposed by Igelnik, and we present several results of decomposition for gray level images. Our goal is to adapt and apply the superposition theorem to image processing, i.e. to decompose an image into simpler functions using Kolmogorov superpositions. We synthetise our observations, before …

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingImage processing[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technologySuperposition theorem01 natural sciences[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[ INFO.INFO-TI ] Computer Science [cs]/Image ProcessingComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATION0202 electrical engineering electronic engineering information engineeringApplied mathematics0101 mathematics[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingMathematicsDiscrete mathematicsSignal processingArtificial neural network010102 general mathematicsApproximation algorithmSpline (mathematics)[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV]Kolmogorov structure function[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]020201 artificial intelligence & image processingHypercube[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing2008 IEEE International Conference on Signal Image Technology and Internet Based Systems
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Roughness evaluation of vine leaf by image processing

2013

International audience; The study of leaf surface roughness is very important in the domain of precision spraying. It is one of the parameters that allow to reduce costs and losses of phytosanitary prod- ucts and to improve the spray accuracy. Moreover, the leaf roughness is related to adhesion mechanisms of liquid on a surface. It can be used to define leaf nature surface (hy- drophilic/hydrophobic). The main goal of this study is thus to estimate and to follow the evolution of leaf roughness using image processing and computer vision. The develop- ment and application of computer vision for measurement of surface leaf roughness using artificial neural networks will be described. The syste…

[ MATH ] Mathematics [math]0106 biological sciences0209 industrial biotechnologyScanning electron microscope[SDV]Life Sciences [q-bio]Computer Vision[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing[MATH] Mathematics [math]02 engineering and technologySurface finishLeaf roughness01 natural sciences[PHYS] Physics [physics][SPI]Engineering Sciences [physics]020901 industrial engineering & automation[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[ SPI ] Engineering Sciences [physics]Surface roughnessComputer vision[MATH]Mathematics [math]ComputingMilieux_MISCELLANEOUS[PHYS]Physics [physics][ PHYS ] Physics [physics]Artificial neural network[STAT]Statistics [stat]Multilayer perceptron[SDE]Environmental SciencesBiological system[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingMaterials science[ STAT ] Statistics [stat][INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing[SPI] Engineering Sciences [physics]IASTEDFast Fourier transformNeural NetworkImage processingImage processing[SDV.BV]Life Sciences [q-bio]/Vegetal BiologyTexturelanguage technologies[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingPrecision agriculturebusiness.industry[STAT] Statistics [stat]Precision agricultureArtificial intelligencebusiness010606 plant biology & botany
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Experimental and numerical enhancement of Vibrational Resonance in a neural circuit

2012

International audience; A neural circuit exactly ruled by the FitzHugh-Nagumo equations is excited by a biharmonic signal of frequencies f and F with respective amplitudes A and B. The magnitude spectrum of the circuit response is estimated at the low frequency driving f and presents a resonant behaviour versus the amplitude B of the high frequency. For the first time, it is shown experimentally that this Vibrational Resonance effect is much more pronounced when the two frequencies are multiple. This novel enhancement is also confirmed by numerical predictions. Applications of this nonlinear effect to the detection of weak stimuli are finally discussed.

[ PHYS.COND.CM-DS-NN ] Physics [physics]/Condensed Matter [cond-mat]/Disordered Systems and Neural Networks [cond-mat.dis-nn]02 engineering and technologyLow frequency01 natural sciencesSignalVibrational ResonanceNuclear magnetic resonance[NLIN.NLIN-PS]Nonlinear Sciences [physics]/Pattern Formation and Solitons [nlin.PS]0103 physical sciences0202 electrical engineering electronic engineering information engineeringVibrational resonance[ NLIN.NLIN-PS ] Nonlinear Sciences [physics]/Pattern Formation and Solitons [nlin.PS][PHYS.COND.CM-DS-NN]Physics [physics]/Condensed Matter [cond-mat]/Disordered Systems and Neural Networks [cond-mat.dis-nn]Electrical and Electronic Engineering010306 general physicsMathematicsQuantitative Biology::Neurons and Cognition020208 electrical & electronic engineering[SPI.TRON]Engineering Sciences [physics]/ElectronicsComputational physics[ SPI.TRON ] Engineering Sciences [physics]/ElectronicsNonlinear systemAmplitudeExcited stateNonlinear resonanceBiharmonic equationNonlinear dynamical systemsFitzHugh-Nagumo
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