Search results for "project"

showing 10 items of 3466 documents

Modeling the insect mushroom bodies: application to a delayed match-to-sample task.

2013

Despite their small brains, insects show advanced capabilities in learning and task solving. Flies, honeybees and ants are becoming a reference point in neuroscience and a main source of inspiration for autonomous robot design issues and control algorithms. In particular, honeybees demonstrate to be able to autonomously abstract complex associations and apply them in tasks involving different sensory modalities within the insect brain. Mushroom Bodies (MBs) are worthy of primary attention for understanding memory and learning functions in insects. In fact, even if their main role regards olfactory conditioning, they are involved in many behavioral achievements and learning capabilities, as …

Arthropod AntennaeInsectaComputer scienceCognitive Neurosciencemedia_common.quotation_subjectModels NeurologicalAction PotentialsInsectGrasshoppersOlfactory Receptor NeuronsTask (project management)03 medical and health sciences0302 clinical medicineStimulus modalityArtificial IntelligenceMemorymedicineLearningAnimalsComputer SimulationDrosophilaMushroom BodiesProblem Solving030304 developmental biologymedia_commonMatch-to-sample taskSpiking neural networkMotor Neurons0303 health sciencesArtificial neural networkbiologybusiness.industryInsect brain; Insect mushroom bodies; Learning; Neural model; Neuroscience; Spiking neurons; Action Potentials; Animals; Arthropod Antennae; Bees; Computer Simulation; Drosophila; Grasshoppers; Insecta; Memory; Motor Neurons; Mushroom Bodies; Nerve Net; Olfactory Receptor Neurons; Problem Solving; Artificial Intelligence; Models Neurological; Neural Networks ComputerBeesAutonomous robotbiology.organism_classificationInsect mushroom bodiesmedicine.anatomical_structureInsect brain; Insect mushroom bodies; LearningMushroom bodiesDrosophilaArtificial intelligenceNeural Networks ComputerNerve NetbusinessInsect brain030217 neurology & neurosurgeryNeuroanatomyNeural networks : the official journal of the International Neural Network Society
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A Fast Imaging Technique Applied to 2D Electrical Resistivity Data

2014

A new technique is proposed to process 2D apparent resistivity datasets, in order to obtain a fast and contrasted resistivity image, useful for a rapid data check in field or as a starting model to constrain the inversion procedure. In the past some modifications to the back-projection algorithm, as well as the use of filtering techniques for the sensitivity matrix were proposed. An implementation of this technique is proposed here, considering a two-step approach. Initially a damped least squares solution is obtained after a full matrix inversion of the linearized geoelectrical problem. Furthermore, on the basis of the results, a subsequent filtering algorithm is applied to the Jacobian ma…

Article SubjectComputer sciencelcsh:QC801-809Apparent resistivityInversion (meteorology)Least squaresSynthetic datalcsh:Geophysics. Cosmic physicssymbols.namesakeGeophysicsElectrical resistivity and conductivityFull matrixSettore GEO/11 - Geofisica ApplicataJacobian matrix and determinantsymbolsImaging techniqueAlgorithmERT back-projection LSQR inversion resistivityWater Science and TechnologyInternational Journal of Geophysics
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Safer chemicals using less animals: kick-off of the European ONTOX project

2021

The 3Rs concept, calling for replacement, reduction and refinement of animal experimentation, is receiving increasing attention around the world, and has found its way to legislation, in particular in the European Union. This is aligned by continuing high-level efforts of the European Commission to support development and implementation of 3Rs methods. In this respect, the European project called "ONTOX: ontology-driven and artificial intelligence-based repeated dose toxicity testing of chemicals for next generation risk assessment" was recently initiated with the goal to provide a functional and sustainable solution for advancing human risk assessment of chemicals without the use of animal…

Artificial intelligenceComputer science010501 environmental sciencesOntology (information science)In Vitro TechniquesAnimal Testing AlternativesToxicology01 natural sciencesRisk Assessment3Rs03 medical and health sciencesIn vitroSAFERAdverse Outcome PathwayToxicity TestsEuropean projectmedia_common.cataloged_instanceAnimalsHumansComputer SimulationEuropean UnionAnimal testingEuropean union0105 earth and related environmental sciencesExposure assessmentmedia_common0303 health sciencesOntologyIn silico030311 toxicology3. Good healthVariety (cybernetics)Gene OntologyRisk analysis (engineering)Systemic toxicityONTOXRisk assessment
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OmniFlowNet: a Perspective Neural Network Adaptation for Optical Flow Estimation in Omnidirectional Images

2021

International audience; Spherical cameras and the latest image processing techniques open up new horizons. In particular, methods based on Convolutional Neural Networks (CNNs) now give excellent results for optical flow estimation on perspective images. However, these approaches are highly dependent on their architectures and training datasets. This paper proposes to benefit from years of improvement in perspective images optical flow estimation and to apply it to omnidirectional ones without training on new datasets. Our network, OmniFlowNet, is built on a CNN specialized in perspective images. Its convolution operation is adapted to be consistent with the equirectangular projection. Teste…

Artificial neural networkComputer sciencebusiness.industryDistortion (optics)Perspective (graphical)[INFO.INFO-RB] Computer Science [cs]/Robotics [cs.RO]ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processing02 engineering and technology010501 environmental sciences01 natural sciencesConvolutional neural networkConvolutionOptical flow estimation0202 electrical engineering electronic engineering information engineering[INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]020201 artificial intelligence & image processingComputer visionArtificial intelligencebusinessProjection (set theory)0105 earth and related environmental sciences
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A Neural Solution for a Mobile Robot Navigation into Unknown Indoor Environments Using Visual Landmarks

1998

In this paper we present a neural solution for a mobile robot navigation into unknown indoor environments by using landmarks. Robot navigation task is implemented by two groups of processes based on MLP neural networks classifiers: a Low Level Vision System performs obstacle avoidance and corridor following, while an High Level Vision System extracts landmarks contents and performs goal directed navigation. A path-planner manages the two navigation systems and interacts with the robot hardware. The proposed solution is very strong and flexible and can be used to drive a mobile robot in real indoor environments. In the paper experimental results are also reported.

Artificial neural networkMachine visionComputer sciencebusiness.industryObstacle avoidanceRobotComputer visionMobile robotArtificial intelligenceVisual landmarksbusinessMobile robot navigationTask (project management)
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An Adaptive Global-Local Memetic Algorithm to Discover Resources in P2P Networks

2007

This paper proposes a neural network based approach for solving the resource discovery problem in Peer to Peer (P2P) networks and an Adaptive Global Local Memetic Algorithm (AGLMA) for performing the training of the neural network. This training is very challenging due to the large number of weights and noise caused by the dynamic neural network testing. The AGLMA is a memetic algorithm consisting of an evolutionary framework which adaptively employs two local searchers having different exploration logic and pivot rules. Furthermore, the AGLMA makes an adaptive noise compensation by means of explicit averaging on the fitness values and a dynamic population sizing which aims to follow the ne…

Artificial neural networkProcess (engineering)Computer sciencebusiness.industryComputer Science::Neural and Evolutionary ComputationComputational intelligencePeer-to-peercomputer.software_genreMachine learningSizingResource (project management)Memetic algorithmNoise (video)Artificial intelligencebusinesscomputer
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A Feed-Forward Neural Network for Robust Segmentation of Color Images

1999

A novel approach for segmentation of color images is proposed. The approach is based on a feed-forward neural network that learns to recognize the hue range of meaningful objects. Experimental results showed that the proposed method is effective and robust even in presence of changing environmental conditions. The described technique has been tested in the framework of the Robot Soccer World Cup Initiative (RoboCup). The approach is fully general and it may be successfully employed in any intermediate level image-processing task, where the color is a meaningful descriptor.

Artificial neural networkbusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONMobile robotTask (project management)Range (mathematics)GeographyFeedforward neural networkRobotComputer visionSegmentationArtificial intelligencebusinessHue
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A Memetic-Neural Approach to Discover Resources in P2P Networks

2008

This chapter proposes a neural network based approach for solving the resource discovery problem in Peer to Peer (P2P) networks and an Adaptive Global Local Memetic Algorithm (AGLMA) for performing in training of the neural network. The neural network, which is a multi-layer perceptron neural network, allows the P2P nodes to efficiently locate resources desired by the user. The necessity of testing the network in various working conditions, aiming to obtain a robust neural network, introduces noise in the objective function. The AGLMA is a memetic algorithm which employs two local search algorithms adaptively activated by an evolutionary framework. These local searchers, having different fe…

Artificial neural networkbusiness.industryProcess (engineering)Computer scienceComputer Science::Neural and Evolutionary ComputationComputational intelligencePeer-to-peercomputer.software_genrePerceptronMachine learningResource (project management)Memetic algorithmLocal search (optimization)Artificial intelligencebusinesscomputer
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Modelo Barcelona y política cultural: usos y abusos de la cultura por parte de un modelo emprendedor de desarrollo local

2015

El Modelo Barcelona de desarrollo local ha sido intensamente debatido· Desde su inicio en los años ochenta hasta la actualidad, diversos autores han analizado sus características como modelo, destacado sus éxitos y también sus puntos débiles. No obstante, menos atención ha recibido la relación que existe entre el modelo de desarrollo local y el modelo de política cultural, a pesar de que Barcelona también es internacionalmente conocida por su dinamismo cultural. De manera habitual, este modelo de política cultural ha sido interpretado como un instrumento en la agenda de desarrollo local. El presente artículo mostrará, a partir de análisis de diversos casos ejemplares, que la política cultur…

Arts facilitieslcsh:NA9000-9428media_common.quotation_subjectLocal DevelopmentBarcelona Modellcsh:Political scienceUrban developmentlcsh:Regional planninglocal developmentlcsh:Urban groups. The city. Urban sociologylcsh:HT165.5-169.9Projection (mathematics)Political sciencelcsh:HT101-395Equipaments culturalsCultural policyDesenvolupament urbàmedia_commonlcsh:NA1-9428Modelo Barcelonapolítica culturalWelfare economicsdesarrollo locallcsh:HT390-395lcsh:City planningCreativitylcsh:Aesthetics of cities. City planning and beautifyingUrban StudiesBarcelona (Catalonia)Barcelona (Catalunya)lcsh:ArchitectureStrengths and weaknesseslcsh:JCultural policy
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Predicting hospital associated disability from imbalanced data using supervised learning.

2019

Hospitalization of elderly patients can lead to serious adverse effects on their functional capability. Identifying the underlying factors leading to such adverse effects is an active area of medical research. The purpose of the current paper is to show the potential of artificial intelligence in the form of machine learning to complement the existing medical research. This is accomplished by studying the outcome of hospitalization of elderly patients as a supervised learning task. A rich set of features characterizing the medical and social situation of elderly patients is leveraged and using confusion matrices, association rule mining, and two different classes of supervised learning algo…

Association rule learningmedicine.medical_treatmentvanhuksetMedicine (miscellaneous)sairaalahoitoOutcome (game theory)Task (project management)03 medical and health sciences0302 clinical medicineArtificial IntelligenceMedicineHumanstoimintarajoitteetDisabled PersonsSet (psychology)Adverse effectFinlandta316030304 developmental biologyAgedta1130303 health sciencesRehabilitationbusiness.industrySupervised learningennusteetta3142medicine.diseaseMedical researchHospitalizationmachine learningkoneoppiminenhospital associated disabilityMedical emergencySupervised Machine Learningtiedonlouhintabusiness030217 neurology & neurosurgeryrandom forestArtificial intelligence in medicine
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