Search results for "Neural Networks"

showing 10 items of 599 documents

Fingerprint classification based on deep learning approaches: Experimental findings and comparisons

2021

Biometric classification plays a key role in fingerprint characterization, especially in the identification process. In fact, reducing the number of comparisons in biometric recognition systems is essential when dealing with large-scale databases. The classification of fingerprints aims to achieve this target by splitting fingerprints into different categories. The general approach of fingerprint classification requires pre-processing techniques that are usually computationally expensive. Deep Learning is emerging as the leading field that has been successfully applied to many areas, such as image processing. This work shows the performance of pre-trained Convolutional Neural Networks (CNNs…

Physics and Astronomy (miscellaneous)BiometricsComputer scienceGeneral Mathematicsfingerprint featuresfingerprint classification; deep learning; convolutional neural networks; fingerprint featuresConvolutional neural networks Deep learning Fingerprint classification Fingerprint featuresImage processing02 engineering and technologyConvolutional neural networkField (computer science)fingerprint classification020204 information systemsconvolutional neural networksQA1-9390202 electrical engineering electronic engineering information engineeringComputer Science (miscellaneous)Reliability (statistics)business.industryDeep learningFingerprint (computing)deep learningPattern recognitionIdentification (information)Chemistry (miscellaneous)Convolutional neural networks; Deep learning; Fingerprint classification; Fingerprint features020201 artificial intelligence & image processingArtificial intelligencebusinessMathematics
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Stringlike Cooperative Motion in a Supercooled Liquid

1998

Extensive molecular dynamics simulations are performed on a glass-forming Lennard-Jones mixture to determine the nature of the cooperative motions occurring in this model fragile liquid. We observe stringlike cooperative molecular motion (``strings'') at temperatures well above the glass transition. The mean length of the strings increases upon cooling, and the string length distribution is found to be nearly exponential.

Physics010304 chemical physicsCondensed matter physicsMathematical modelGeneral Physics and AstronomyCondensed Matter::Disordered Systems and Neural Networks01 natural sciences3. Good healthExponential functionCondensed Matter::Soft Condensed MatterMolecular dynamics0103 physical sciencesQuasiparticleRelaxation (physics)Dynamical heterogeneity010306 general physicsGlass transitionSupercoolingPhysical Review Letters
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The phase diagram of the multi-dimensional Anderson localization via analytic determination of Lyapunov exponents

2004

The method proposed by the present authors to deal analytically with the problem of Anderson localization via disorder [J.Phys.: Condens. Matter {\bf 14} (2002) 13777] is generalized for higher spatial dimensions D. In this way the generalized Lyapunov exponents for diagonal correlators of the wave function, $$, can be calculated analytically and exactly. This permits to determine the phase diagram of the system. For all dimensions $D > 2$ one finds intervals in the energy and the disorder where extended and localized states coexist: the metal-insulator transition should thus be interpreted as a first-order transition. The qualitative differences permit to group the systems into two classes…

PhysicsAnderson localizationGroup (mathematics)DiagonalFOS: Physical sciencesLyapunov exponentFunction (mathematics)Disordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksCondensed Matter PhysicsElectronic Optical and Magnetic Materialssymbols.namesakePercolationsymbolsCritical dimensionMathematical physicsPhase diagram
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Spatial multifractal properties of wave packets in the Anderson model of localization.

1993

The multifractal properties of electronic wave functions in disordered samples are investigated. In a given energy range all eigenstates are determined for the same disorder configuration in the Anderson model of localization. It is shown that the singularity spectrum and the generalized dimensions change only slowly with energy, aside from statistical fluctuations. More important, the wave packet constructed by linear combination of the eigenstates shows quantitatively the same multifractal properties. Consequences for the transport properties of electronic states in disordered systems are discussed.

PhysicsAnderson localizationQuantum mechanicsWave packetMultifractal systemElectronic structureStatistical physicsStatistical fluctuationsSingularity spectrumWave functionCondensed Matter::Disordered Systems and Neural NetworksAnderson impurity modelPhysical review. B, Condensed matter
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The relaxation dynamics of a viscous silica melt: II The intermediate scattering functions

2001

We use molecular dynamics computer simulations to study the relaxation dynamics of a viscous melt of silica. The coherent and incoherent intermediate scattering functions, F_d(q,t) and F_s(q,t), show a crossover from a nearly exponential decay at high temperatures to a two-step relaxation at low temperatures. Close to the critical temperature of mode-coupling theory (MCT) the correlators obey in the alpha-regime the time temperature superposition principle (TTSP) and show a weak stretching. We determine the wave-vector dependence of the stretching parameter and find that for F_d(q,t) it shows oscillations which are in phase with the static structure factor. The temperature dependence of the…

PhysicsArrhenius equationCondensed matter physicsStatistical Mechanics (cond-mat.stat-mech)ScatteringThermodynamicsFOS: Physical sciencesDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksFick's laws of diffusionPower lawsymbols.namesakeTime–temperature superpositionsymbolsRelaxation (physics)Exponential decayStructure factorCondensed Matter - Statistical Mechanics
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Evidence against a glass transition in the 10-state short range Potts glass

2002

We present the results of Monte Carlo simulations of two different 10-state Potts glasses with random nearest neighbor interactions on a simple cubic lattice. In the first model the interactions come from a \pm J distribution and in the second model from a Gaussian one, and in both cases the first two moments of the distribution are chosen to be equal to J_0=-1 and Delta J=1. At low temperatures the spin autocorrelation function for the \pm J model relaxes in several steps whereas the one for the Gaussian model shows only one. In both systems the relaxation time increases like an Arrhenius law. Unlike the infinite range model, there are only very weak finite size effects and there is no evi…

PhysicsArrhenius equationStatistical Mechanics (cond-mat.stat-mech)GaussianMonte Carlo methodAutocorrelationFOS: Physical sciencesGeneral Physics and AstronomyDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural Networksk-nearest neighbors algorithmsymbols.namesakesymbolsStatistical physicsGlass transitionGaussian network modelCondensed Matter - Statistical MechanicsSpin-½
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Nonlinear effects in charge stabilized colloidal suspensions

2006

Molecular Dynamics simulations are used to study the effective interactions in charged stabilized colloidal suspensions. For not too high macroion charges and sufficiently large screening, the concept of the potential of mean force is known to work well. In the present work, we focus on highly charged macroions in the limit of low salt concentrations. Within this regime, nonlinear corrections to the celebrated DLVO theory [B. Derjaguin and L. Landau, Acta Physicochem. USSR {\bf 14}, 633 (1941); E.J.W. Verwey and J.T.G. Overbeck, {\em Theory of the Stability of Lyotropic Colloids} (Elsevier, Amsterdam, 1948)] have to be considered. For non--bulklike systems, such as isolated pairs or triples…

PhysicsCharge densityFOS: Physical sciencesCharge (physics)Disordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Soft Condensed MatterCondensed Matter - Disordered Systems and Neural NetworksIonCondensed Matter::Soft Condensed MatterRenormalizationNonlinear systemColloidClassical mechanicsChemical physicsExcluded volumeSoft Condensed Matter (cond-mat.soft)Anisotropy
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Identification of strong and weak interacting two level systems in KBr:CN

2010

Tunneling two level systems (TLSs) are believed to be the source of phenomena such as the universal low temperature properties in disordered and amorphous solids, and $1/f$ noise. The existence of these phenomena in a large variety of dissimilar physical systems testifies for the universal nature of the TLSs, which however, is not yet known. Following a recent suggestion that attributes the low temperature TLSs to inversion pairs [M. Schechter and P.C.E. Stamp, arXiv:0910.1283.] we calculate explicitly the TLS-phonon coupling of inversion symmetric and asymmetric TLSs in a given disordered crystal. Our work (a) estimates parameters that support the theory in M. Schechter and P.C.E. Stamp, a…

PhysicsCondensed Matter - Materials ScienceCondensed matter physicsCondensed Matter - Mesoscale and Nanoscale PhysicsPhysical systemMaterials Science (cond-mat.mtrl-sci)FOS: Physical sciencesGeneral Physics and AstronomyDisordered Systems and Neural Networks (cond-mat.dis-nn)02 engineering and technologyCondensed Matter - Disordered Systems and Neural Networks021001 nanoscience & nanotechnology01 natural sciencesAmorphous solidMesoscale and Nanoscale Physics (cond-mat.mes-hall)0103 physical sciences010306 general physics0210 nano-technologyQuantum tunnelling
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Analytical representations for relaxation functions of glasses

2002

Analytical representations in the time and frequency domains are derived for the most frequently used phenomenological fit functions for non-Debye relaxation processes. In the time domain the relaxation functions corresponding to the complex frequency dependent Cole-Cole, Cole-Davidson and Havriliak-Negami susceptibilities are also represented in terms of $H$-functions. In the frequency domain the complex frequency dependent susceptibility function corresponding to the time dependent stretched exponential relaxation function is given in terms of $H$-functions. The new representations are useful for fitting to experiment.

PhysicsCondensed Matter - Materials ScienceMaterials Science (cond-mat.mtrl-sci)FOS: Physical sciencesFunction (mathematics)Disordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksCondensed Matter PhysicsElectronic Optical and Magnetic MaterialsExponential functionFrequency domainMaterials ChemistryCeramics and CompositesRelaxation (physics)Time domainStatistical physicsSusceptibility function
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Lattice Boltzmann versus Molecular Dynamics simulations of nanoscale hydrodynamic flows

2006

A fluid flow in a simple dense liquid, passing an obstacle in a two-dimensional thin film geometry, is simulated by Molecular Dynamics (MD) computer simulation and compared to results of Lattice Boltzmann (LB) simulations. By the appropriate mapping of length and time units from LB to MD, the velocity field as obtained from MD is quantitatively reproduced by LB. The implications of this finding for prospective LB-MD multiscale applications are discussed.

PhysicsCondensed Matter - Materials ScienceNanostructureLattice Boltzmann methodsMaterials Science (cond-mat.mtrl-sci)FOS: Physical sciencesGeneral Physics and AstronomyDisordered Systems and Neural Networks (cond-mat.dis-nn)MechanicsCondensed Matter - Disordered Systems and Neural NetworksNanostructuresMolecular dynamicsModels ChemicalFluid dynamicsThermodynamicsComputer SimulationVector fieldStatistical physicsThin filmNanoscopic scale
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