Search results for "NEURAL NETWORK"

showing 10 items of 1385 documents

Spiking Neural Networks models targeted for implementation on Reconfigurable Hardware

2017

La tesis presentada se centra en la denominada tercera generación de redes neuronales artificiales, las Redes Neuronales Spiking (SNN) también llamadas ‘de espigas’ o ‘de eventos’. Este campo de investigación se convirtió en un tema popular e importante en la última década debido al progreso de la neurociencia computacional. Las Redes Neuronales Spiking, que tienen no sólo la plasticidad espacial sino también temporal, ofrecen una alternativa prometedora a las redes neuronales artificiales clásicas (ANN) y están más cerca de la operación real de las neuronas biológicas ya que la información se codifica y transmite usando múltiples espigas o eventos en forma de trenes de pulsos. Este campo h…

330406330703330416machine learningspiking neural networks330793neural networksfpgasnn120318
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A neural architecture for 3D segmentation

2003

An original neural scheme for segmentation of range data is presented, which is part of a more general 3D vision system for robotic applications. The entire process relies on a neural architecture aimed to perform first order image irradiance analysis, that is local estimation of magnitude and orientation of the image irradiance gradient.In the case of dense 3D data, irradiance is replaced by depth information so irradiance analysis of these pseudo-images provides knowledge about the actual curvature of the acquired surfaces. In particular, boundaries and contours due to mutual occlusions can be detected very well while there are no false contours due to rapid changing in brightness or colo…

3D segmentationNULLneural networks
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Focal Cortical Lesions Induce Bidirectional Changes in the Excitability of Fast Spiking and Non Fast Spiking Cortical Interneurons

2014

A physiological brain function requires neuronal networks to operate within a well-defined range of activity. Indeed, alterations in neuronal excitability have been associated with several pathological conditions, ranging from epilepsy to neuropsychiatric disorders. Changes in inhibitory transmission are known to play a key role in the development of hyperexcitability. However it is largely unknown whether specific interneuronal subpopulations contribute differentially to such pathological condition. In the present study we investigated functional alterations of inhibitory interneurons embedded in a hyperexcitable cortical circuit at the border of chronically induced focal lesions in mouse …

500 Naturwissenschaften und Mathematik::570 Biowissenschaften; Biologie570Neural NetworksPostsynaptic CurrentExcitotoxicity610lcsh:MedicineNeurophysiologyAction PotentialsNeural Homeostasis600 Technik Medizin angewandte Wissenschaften::610 Medizin und Gesundheitmedicine.disease_causeInhibitory postsynaptic potentialMiceEpilepsyInterneuronsmedicineBiological neural networkAnimalslcsh:ScienceVisual CortexCerebral CortexMembrane potentialMultidisciplinarymusculoskeletal neural and ocular physiologylcsh:RNeurotransmissionBiology and Life SciencesExcitatory Postsynaptic Potentialsmedicine.diseaseVisual cortexmedicine.anatomical_structurenervous systemCellular NeuroscienceExcitatory postsynaptic potentiallcsh:QNeuroscienceResearch ArticleNeurosciencePLoS ONE
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Synaptic scaling generically stabilizes circuit connectivity

2011

Neural systems regulate synaptic plasticity avoiding overly strong growth or shrinkage of the connections, thereby keeping the circuit architecture operational. Accordingly, several experimental studies have shown that synaptic weights increase only in direct relation to their current value, resulting in reduced growth for stronger synapses [1]. It is, however, difficult to extract from these studies unequivocal evidence about the underlying biophysical mechanisms that control weight growth. The theoretical neurosciences have addressed this problem by exploring mechanisms for synaptic weight change that contain limiting factors to regulate growth [2]. The effectiveness of these mechanisms i…

573.8Computer science612.8612Plasticity573530lcsh:RC321-57103 medical and health sciencesCellular and Molecular NeuroscienceSynaptic weight0302 clinical medicineHomeostatic plasticityBiological neural networklcsh:Neurosciences. Biological psychiatry. Neuropsychiatry030304 developmental biology0303 health sciencesSynaptic scalingGeneral NeuroscienceWeight changelcsh:QP351-495Hebbian theorylcsh:Neurophysiology and neuropsychologyPoster PresentationSynaptic plasticityNeuroscience030217 neurology & neurosurgeryBMC Neuroscience
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Learning automata based energy-efficient AI hardware design for IoT applications

2020

Energy efficiency continues to be the core design challenge for artificial intelligence (AI) hardware designers. In this paper, we propose a new AI hardware architecture targeting Internet of Things applications. The architecture is founded on the principle of learning automata, defined using propositional logic. The logic-based underpinning enables low-energy footprints as well as high learning accuracy during training and inference, which are crucial requirements for efficient AI with long operating life. We present the first insights into this new architecture in the form of a custom-designed integrated circuit for pervasive applications. Fundamental to this circuit is systematic encodin…

7621003Computer scienceGeneral MathematicsDesign flow1006General Physics and Astronomy02 engineering and technologySoftwareRobustness (computer science)0202 electrical engineering electronic engineering information engineeringField-programmable gate arrayenergy efficiencyHardware architectureArtificial neural networkLearning automata52business.industryTsetlin machines020208 electrical & electronic engineeringGeneral Engineeringartificial intelligence hardware designArticlesneural networksAutomation020202 computer hardware & architecturebusinessComputer hardwareResearch ArticlePhilosophical transactions. Series A, Mathematical, physical, and engineering sciences
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Towards a Comprehension of University Dropout in Catalonia: the Case of Universitat Autònoma de Barcelona

2015

The article presents the results of a research that aims to unfold the reasons behind students’ dropout at the Autonomous University of Barcelona (UAB). Data is analyzed, and interviews and focus groups with students who have dropout, study degree’s coordinators and institutional authorities are carried out. Results indicate that part of the abandonment taking place is voluntary, natural and even necessary, when the student does not enter the desired option or discovers that the studies do not fi t with their vocational interests, but it also represents a misalignment between the academic offer and the students’ capabilities, performance and motivation.

Abandonment (legal)abandonoFocus groupretenciónEducationVocational educationPedagogyComputingMilieux_COMPUTERSANDEDUCATIONestudiantesSociologylcsh:LDropout (neural networks)universidadlcsh:EducationEstudios sobre Educación
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Acoustic characterization of Silica aerogel clamped plates for perfect absorption purpose

2017

International audience; Silica aerogel has been widely studied as bulk material for its extremely low density and thermal conductivity. Plates or membranes made of this extremely soft materials exhibits interesting properties for sound absorption. A novel signal processing method for the characterization of an acoustic metamaterial made of silica aerogel clamped plates is presented. The acoustic impedance of a silica aerogel clamped plate is derived from the elastic theory for the flexural waves, while the transfer matrix method is used to model reflection and transmission coefficients of a single plate. Experimental results are obtained by using an acoustic impedance tube. The difference b…

Absorption (acoustics)Materials scienceAcoustics and UltrasonicsPhysics::Instrumentation and DetectorsTransfer-matrix method (optics)Physics::Optics01 natural sciencesCondensed Matter::Disordered Systems and Neural Networks03 medical and health sciences0302 clinical medicineThermal conductivityArts and Humanities (miscellaneous)0103 physical sciencesReflection coefficientComposite material030223 otorhinolaryngology010301 acousticsComputingMilieux_MISCELLANEOUSMetamaterialAerogel[PHYS.MECA]Physics [physics]/Mechanics [physics][PHYS.MECA.ACOU]Physics [physics]/Mechanics [physics]/Acoustics [physics.class-ph]Condensed Matter::Soft Condensed MatterReflection (mathematics)[PHYS.MECA] Physics [physics]/Mechanics [physics]Acoustic impedance[PHYS.MECA.ACOU] Physics [physics]/Mechanics [physics]/Acoustics [physics.class-ph]
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OH-related Infrared Absorption Bands in Oxide Glasses

2005

We report the infrared activity, in the spectral region of the OH stretching modes, of different composite silicate glasses whose chemical composition is established by X-ray fluorescence measurements. The analysis of the absorption line profiles is made in terms of different spectral contributions, Gaussian in shape. The comparison with analogous spectra obtained in vitreous silica samples with impurity concentrations < 100 part per million moles is evidence of the effects of the different oxides on the vibrational properties of the OH groups. In particular, for oxide glasses a red shift of the composite band at about 3670 cm(-1), assigned to the OH stretching modes of free Si-OH groups an…

Absorption spectroscopyInfraredFTIR AbsorptionOxide glasseOxideAnalytical chemistryX-ray fluorescenceInfrared spectroscopyCondensed Matter PhysicsCondensed Matter::Disordered Systems and Neural NetworksSylanol groupsSilicateSpectral lineSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Settore FIS/03 - Fisica Della MateriaElectronic Optical and Magnetic Materialschemistry.chemical_compoundchemistryImpurityHydroxyl groupFTIR spectroscopy.Materials ChemistryCeramics and Compositessilicate glasse
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Mini-COVIDNet: Efficient Lightweight Deep Neural Network for Ultrasound Based Point-of-Care Detection of COVID-19

2021

Lung ultrasound (US) imaging has the potential to be an effective point-of-care test for detection of COVID-19, due to its ease of operation with minimal personal protection equipment along with easy disinfection. The current state-of-the-art deep learning models for detection of COVID-19 are heavy models that may not be easy to deploy in commonly utilized mobile platforms in point-of-care testing. In this work, we develop a lightweight mobile friendly efficient deep learning model for detection of COVID-19 using lung US images. Three different classes including COVID-19, pneumonia, and healthy were included in this task. The developed network, named as Mini-COVIDNet, was bench-marked with …

Acoustics and UltrasonicsCoronavirus disease 2019 (COVID-19)Computer sciencePoint-of-Care SystemsLatency (audio)detectionlung ultrasound (US) imaging01 natural sciences0103 physical sciencesImage Interpretation Computer-AssistedComputer-Assisted/methodsHumansElectrical and Electronic Engineering010301 acousticsInstrumentationImage InterpretationPoint of careUltrasonographyArtificial neural networkbusiness.industrySARS-CoV-2Deep learningImage Interpretation Computer-Assisted/methodsVDP::Technology: 500COVID-19deep learningUltrasonography/methodsLung ultrasoundCoronavirusTask (computing)point-of-care testingSoftware deploymentEmbedded systemCOVID-19/diagnostic imagingArtificial intelligencebusiness
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An ASSOM neural network to represent actions performed by an autonomous agent

1997

An ASSOM neural network to describe the action performed by an autonomous reactive agent is proposed. The neural network receives in input the sequences of data acquired by the agent internal sensors and it classifies them by generating the corresponding symbolic assertions. Experimental results performed on a RWI B12 autonomous robot are reported.

Action (philosophy)Artificial neural networkComputer sciencebusiness.industryControl systemAutonomous agentRoboticsComputingMethodologies_GENERALArtificial intelligenceAutonomous robotbusiness
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