Search results for "Image processing"

showing 10 items of 3285 documents

Learning Automata-based Misinformation Mitigation via Hawkes Processes

2021

AbstractMitigating misinformation on social media is an unresolved challenge, particularly because of the complexity of information dissemination. To this end, Multivariate Hawkes Processes (MHP) have become a fundamental tool because they model social network dynamics, which facilitates execution and evaluation of mitigation policies. In this paper, we propose a novel light-weight intervention-based misinformation mitigation framework using decentralized Learning Automata (LA) to control the MHP. Each automaton is associated with a single user and learns to what degree that user should be involved in the mitigation strategy by interacting with a corresponding MHP, and performing a joint ra…

Computer Networks and CommunicationsComputer scienceDistributed computingStochastic optimizationSocial media Misinformation02 engineering and technologyCrisis mitigationArticleTheoretical Computer ScienceLearning automata020204 information systemsConvergence (routing)0202 electrical engineering electronic engineering information engineeringState spaceSocial mediaMisinformationVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550Social networkLearning automatabusiness.industryAutomaton020201 artificial intelligence & image processingStochastic optimizationbusinessHawkes processesSoftwareInformation Systems
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An Scalable matrix computing unit architecture for FPGA and SCUMO user design interface

2019

High dimensional matrix algebra is essential in numerous signal processing and machine learning algorithms. This work describes a scalable square matrix-computing unit designed on the basis of circulant matrices. It optimizes data flow for the computation of any sequence of matrix operations removing the need for data movement for intermediate results, together with the individual matrix operations’ performance in direct or transposed form (the transpose matrix operation only requires a data addressing modification). The allowed matrix operations are: matrix-by-matrix addition, subtraction, dot product and multiplication, matrix-by-vector multiplication, and matrix by scalar multiplication.…

Computer Networks and CommunicationsComputer scienceMathematicsofComputing_NUMERICALANALYSISSistemes informàticslcsh:TK7800-836002 engineering and technologyScalar multiplicationComputational scienceMatrix (mathematics)matrix-computing unitTranspose0202 electrical engineering electronic engineering information engineeringmatrix processorElectrical and Electronic EngineeringCirculant matrixcirculant matricesFPGA020208 electrical & electronic engineeringlcsh:ElectronicsDot productMatrix multiplicationArquitectura d'ordinadorsHardware and ArchitectureControl and Systems Engineeringmatrix arithmeticSignal Processing020201 artificial intelligence & image processingMultiplicationhardware implementation
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Remote interspecies interactions: Improving humans and animals wellbeing through mobile playful spaces

2019

[EN] Play is an essential activity for both humans and animals as it provides stimulation and favors cognitive, physical and social development. This paper proposes a novel pervasive playful environment that allows hospitalized children to participate in remote interspecies play with dogs in a dog daycare facility, while it also allows the dogs to play by themselves with the pervasive system. The aim of this playful interactive space is to help improving both children¿s and animal¿s wellbeing and their relationships by means of technologically mediated play, while creating a solid knowledge base to define the future of pervasive interactive environments for animals.

Computer Networks and CommunicationsComputer scienceMobile application02 engineering and technologySpace (commercial competition)Child computer interactionAnimal computer interactionHuman–computer interactionInteractive environment0202 electrical engineering electronic engineering information engineeringChild computer interactionRemote playbusiness.industrySocial changeComputingMilieux_PERSONALCOMPUTING020206 networking & telecommunicationsCognitionComputer Science ApplicationsAnimal computer interactionKnowledge baseHardware and Architecture020201 artificial intelligence & image processingbusinessLENGUAJES Y SISTEMAS INFORMATICOSSoftwareInformation Systems
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Moving Learning Machine Towards Fast Real-Time Applications: A High-Speed FPGA-based Implementation of the OS-ELM Training Algorithm

2018

Currently, there are some emerging online learning applications handling data streams in real-time. The On-line Sequential Extreme Learning Machine (OS-ELM) has been successfully used in real-time condition prediction applications because of its good generalization performance at an extreme learning speed, but the number of trainings by a second (training frequency) achieved in these continuous learning applications has to be further reduced. This paper proposes a performance-optimized implementation of the OS-ELM training algorithm when it is applied to real-time applications. In this case, the natural way of feeding the training of the neural network is one-by-one, i.e., training the neur…

Computer Networks and CommunicationsComputer scienceReal-time computingParameterized complexitylcsh:TK7800-836002 engineering and technologyextreme learning machine0202 electrical engineering electronic engineering information engineeringSensitivity (control systems)Electrical and Electronic EngineeringEnginyeria d'ordinadorsField-programmable gate arrayFPGAExtreme learning machineEnginyeria elèctricaArtificial neural networkData stream mininglcsh:Electronics020206 networking & telecommunicationsOS-ELMreal-time learningHardware and ArchitectureControl and Systems Engineeringon-chip trainingSignal Processingon-line learning020201 artificial intelligence & image processingDistributed memoryonline sequential ELMhardware implementationAlgorithm
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Noise assisted image processing by ensembles of R-SETs

2017

AbstractWe study how noise can assist the processing of an image in a resistance-single electron transistor (R-SET) model. The image is an 8-bit black and white picture. Every grey level is codified linearly into a sub-threshold input potential applied for a prescribed time window to an ensemble of R-SETs that transforms it into a spiking frequency. The addition of a background white noise potential of high amplitude permits the ensemble to process the image by means of the stochastic resonance phenomenon. Aside from the positive aspects, we analyse the negative impact of using noise and how we can minimize it using redundancy and a longer measuring time. The results are compared with the c…

Computer Networks and CommunicationsComputer scienceStochastic resonancebusiness.industryImage processing02 engineering and technologyWhite noise021001 nanoscience & nanotechnologyMachine learningcomputer.software_genre03 medical and health sciencesNoise0302 clinical medicineRedundancy (information theory)Dark-frame subtractionImage noiseMedian filterArtificial intelligence0210 nano-technologybusinesscomputerAlgorithm030217 neurology & neurosurgerySoftwareInternational Journal of Parallel, Emergent and Distributed Systems
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A group-based wireless body sensors network using energy harvesting for soccer team monitoring

2016

[EN] In team-based sports, it is difficult to monitor physical state of each athlete during the match. Wearable body sensors with wireless connections allow having low-power and low-size devices, that may use energy harvesting, but with low radio coverage area but the main issue comes from the mobility. This paper presents a wireless body sensors network for soccer team players' monitoring. Each player has a body sensor network that use energy harvesting and each player will be a node in the wireless sensor network. This proposal is based on the zone mobility of the players and their dynamism. It allows knowing the physical state of each player during the whole match. Having fast updates an…

Computer Networks and CommunicationsComputer scienceWearable computer02 engineering and technologyGroup-based wireless sensor networkTEORIA DE LA SEÑAL Y COMUNICACIONES0202 electrical engineering electronic engineering information engineeringWirelessDynamismElectrical and Electronic Engineeringbusiness.industryNode (networking)020206 networking & telecommunicationsINGENIERIA TELEMATICAWSNComputer Science ApplicationsKey distribution in wireless sensor networksControl and Systems EngineeringEmbedded system020201 artificial intelligence & image processingState (computer science)Wireless body sensor networkMobilitysoccerbusinessEnergy harvestingWireless sensor networkComputer network
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Performance comparison of container orchestration platforms with low cost devices in the fog, assisting Internet of Things applications

2020

Abstract In the last decade there has been an increasing interest and demand on the Internet of Things (IoT) and its applications. But, when a high level of computing and/or real time processing is required for these applications, different problems arise due to their requirements. In this context, low cost autonomous and distributed Small Board Computers (SBC) devices, with processing, storage capabilities and wireless communications can assist these IoT networks. Usually, these SBC devices run an operating system based on Linux. In this scenario, container-based technologies and fog computing are an interesting approach and both have led to a new paradigm in how devices cooperate, improvi…

Computer Networks and CommunicationsComputer sciencebusiness.industryDistributed computing020206 networking & telecommunications02 engineering and technologyLoad balancing (computing)Virtualizationcomputer.software_genreNetwork topologyComputer Science ApplicationsHardware and ArchitecturePerformance comparisonScalability0202 electrical engineering electronic engineering information engineeringWireless020201 artificial intelligence & image processingOrchestration (computing)businessInternet of ThingscomputerJournal of Network and Computer Applications
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Analysis of HMAX Algorithm on Black Bar Image Dataset

2020

An accurate detection and classification of scenes and objects is essential for interacting with the world, both for living beings and for artificial systems. To reproduce this ability, which is so effective in the animal world, numerous computational models have been proposed, frequently based on bioinspired, computational structures. Among these, Hierarchical Max-pooling (HMAX) is probably one of the most important models. HMAX is a recognition model, mimicking the structures and functions of the primate visual cortex. HMAX has already proven its effectiveness and versatility. Nevertheless, its computational structure presents some criticalities, whose impact on the results has never been…

Computer Networks and CommunicationsComputer sciencelcsh:TK7800-8360Context (language use)02 engineering and technologySet (abstract data type)03 medical and health sciences0302 clinical medicineGabor filterBBIDEncoding (memory)0202 electrical engineering electronic engineering information engineeringElectrical and Electronic EngineeringModularity (networks)Contextual image classificationbusiness.industrylcsh:ElectronicsPattern recognitioncomputational modelBlack Bar Image DatasetHardware and ArchitectureControl and Systems EngineeringHMAXSignal Processingtexture classification020201 artificial intelligence & image processingArtificial intelligencerecognitionbusiness030217 neurology & neurosurgeryimage classificationElectronics
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Communication and security in communicating things networks

2020

International audience

Computer Networks and CommunicationsHardware and ArchitectureComputer science0202 electrical engineering electronic engineering information engineering020206 networking & telecommunications020201 artificial intelligence & image processing[INFO]Computer Science [cs]02 engineering and technologyComputer securitycomputer.software_genrecomputerSoftwareComputingMilieux_MISCELLANEOUS
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Perceptual adaptive insensitivity for support vector machine image coding.

2005

Support vector machine (SVM) learning has been recently proposed for image compression in the frequency domain using a constant epsilon-insensitivity zone by Robinson and Kecman. However, according to the statistical properties of natural images and the properties of human perception, a constant insensitivity makes sense in the spatial domain but it is certainly not a good option in a frequency domain. In fact, in their approach, they made a fixed low-pass assumption as the number of discrete cosine transform (DCT) coefficients to be used in the training was limited. This paper extends the work of Robinson and Kecman by proposing the use of adaptive insensitivity SVMs [2] for image coding u…

Computer Networks and CommunicationsImage processingPattern Recognition AutomatedArtificial IntelligenceDistortionImage Interpretation Computer-AssistedDiscrete cosine transformComputer SimulationMathematicsModels StatisticalArtificial neural networkbusiness.industryPattern recognitionSignal Processing Computer-AssistedGeneral MedicineData CompressionComputer Science ApplicationsSupport vector machineFrequency domainVisual PerceptionA priori and a posterioriArtificial intelligencebusinessSoftwareAlgorithmsImage compressionIEEE transactions on neural networks
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