Search results for "video"

showing 10 items of 1348 documents

Portāla YouTube patēriņa paradumi un lietošanas motivācija vidusskolas vecuma jauniešu vidū

2016

Bakalaura darba „Portāla Youtube patēriņa paradumi un lietošanas motivācija vidusskolas vecuma jauniešu vidū” mērķis ir veicot padziļinātās intervijas un anketēšanu noskaidrot kādām darbībām portāls Youtube galvenokārt tiek izmantots un kādi ir tā izmantošanas paradumi un motivācija Latvijas vidusskolas vecuma jauniešu vidū. Darbs sastāv no 7 nodaļām. Teorētisko daļu sastāda nodaļas par Web 2.0, portālu Youtube, lietojuma un apmierinātības teoriju, bērnu un jauniešu interneta lietojumu. Metodoloģijas daļa apskata darbā izmantotās metodes, jauktā pētniecības metode, dziļās intervijas un anketēšana. 6. un 7. nodaļu sastāda pētījuma gaitā iegūto datu analīzes. Darbā tika secināts, ka vidusskol…

YoutubelietojumsvajadzībasKomunikācijas zinātnemotivācijavideo
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Searches for heavy neutrinos from Z decays

1992

We have searched for possible fourth family heavy neutrinos, pair produced in Z0 decays, in a sample of about 112 000 hadronic Z0 final states collected with the DELPHI detector. For all mixing matrix elements we exclude a new Dirac neutrino lighter than 44.5 GeV at a 95% confidence level, if the neutrino couples to the electron or muon family, and lighter than 44.0 GeV, if the neutrino couples to the tau family. Depending on the values of the mixing element and to which lepton family the neutrino couples, we obtain mass limits up to 46.2 GeV. For all mixing matrix elements we exclude a new Majorana neutrino lighter than 39.0 GeV, if it couples to the electron or the muon family, and lighte…

Z-PEAK; LEPTONS; RESONANCE; LIMITS; QUARKSNuclear and High Energy PhysicsParticle physicsPhysics::Instrumentation and DetectorsAstrophysics::High Energy Astrophysical PhenomenaElectron–positron annihilationHadron01 natural sciencesNuclear physicsLIMITS0103 physical sciences[PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex]QUARKSNuclear Experiment010306 general physicsMixing (physics)PhysicsMuon010308 nuclear & particles physicsDirac (video compression format)High Energy Physics::PhenomenologyRESONANCEZ-PEAKMAJORANALEPTONSPhysique des particules élémentairesFísica nuclearHigh Energy Physics::ExperimentNeutrinoParticle Physics - ExperimentLepton
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Towards a Novel Approach to Multimedia Data Mixed Fragmentation

2009

International audience; Distributed multimedia applications have emerged at an increasing rate during the last decade in several domains (video conferencing, e-health, virtual meeting rooms, etc). This has created several new challenging problems related to the data integration and fragmentation, user-oriented and adaptive interfaces, real time and network performances, etc. In this paper, we focus on the problem of data(base) fragmentation in a multimedia context. We recall in this respect that data fragmentation consists of reducing irrelevant data accesses by grouping data frequently accessed together in dedicated segments. We mainly address the issue of query and predicate implication r…

[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR][INFO.INFO-WB] Computer Science [cs]/WebComputer science[ INFO.INFO-WB ] Computer Science [cs]/Web[SCCO.COMP]Cognitive science/Computer science02 engineering and technologycomputer.software_genreMultimedia DistanceVideoconferencing[SCCO.COMP] Cognitive science/Computer science020204 information systems0202 electrical engineering electronic engineering information engineering[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB]Data partitioningData PartitionQuery Implication[ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM][INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM][INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]MultimediaFunctional Dependency[INFO.INFO-WB]Computer Science [cs]/WebFragmentation (computing)[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM]Multimedia FragmentationPartition (database)Predicate (grammar)[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB][INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR][ SCCO.COMP ] Cognitive science/Computer science020201 artificial intelligence & image processing[INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]computerData integration
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A 1.3 megapixel FPGA-based smart camera for high dynamic range real time video

2013

International audience; A camera is able to capture only a part of a high dynamic range scene information. The same scene can be fully perceived by the human visual system. This is true especially for real scenes where the difference in light intensity between the dark areas and bright areas is high. The imaging technique which can overcome this problem is called HDR (High Dynamic Range). It produces images from a set of multiple LDR images (Low Dynamic Range), captured with different exposure times. This technique appears as one of the most appropriate and a cheap solution to enhance the dynamic range of captured environments. We developed an FPGA-based smart camera that produces a HDR liv…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer science[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONVideo camera02 engineering and technologyTone mapping[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processinglaw.invention[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processinglaw0202 electrical engineering electronic engineering information engineeringComputer visionSmart cameraHigh dynamic range[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingCMOS sensorbusiness.industry020206 networking & telecommunicationsFrame rateLight intensityHuman visual system model020201 artificial intelligence & image processingArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Smart camera design for realtime High Dynamic Range imaging

2011

International audience; Many camera sensors suffer from limited dynamic range. The result is that there is a lack of clear details in displayed images and videos. This paper describes our approach to generate high dynamic range (HDR) from an image sequence while modifying exposure times for each new frame. For this purpose, we propose an FPGA-based architecture that can produce a real-time high dynamic range video from successive image acquisition. Our hardware platform is build around a standard low dynamic range CMOS sensor and a Virtex 5 FPGA board. The CMOS sensor is a EV76C560 provided by e2v. This 1.3 Megapixel device offers novel pixel integration/readout modes and embedded image pre…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingACM IEEEImagingVideosHardware[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingHigh-dynamic-range imaging0202 electrical engineering electronic engineering information engineeringComputer visionSmart cameraImage sensorImage resolutionHigh dynamic range[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingPipelinesCMOS sensorDynamic rangePixelbusiness.industrySensors020208 electrical & electronic engineeringReal time systems020207 software engineeringFrame rate[SPI.TRON]Engineering Sciences [physics]/Electronics[ SPI.TRON ] Engineering Sciences [physics]/ElectronicsArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Preprocessing of region of interest localization based on local surface curvature analysis for three-dimensional reconstruction with multiresolution

2009

We present an approach to integrate a preprocessing step of the region of interest ROI localization into 3-D scanners laser or ste- reoscopic. The definite objective is to make the 3-D scanner intelligent enough to localize rapidly in the scene, during the preprocessing phase, the regions with high surface curvature, so that precise scanning will be done only in these regions instead of in the whole scene. In this way, the scanning time can be largely reduced, and the results contain only per- tinent data. To test its feasibility and efficiency, we simulated the prepro- cessing process under an active stereoscopic system composed of two cameras and a video projector. The ROI localization is…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION3d scanningStereoscopyImage processing0102 computer and information sciences02 engineering and technologyIterative reconstruction[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingCurvature01 natural sciencesVideo projectorsurface curvaturelaw.invention[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingRegion of interestlaw0202 electrical engineering electronic engineering information engineeringPreprocessorComputer visionImage resolution[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingComputingMethodologies_COMPUTERGRAPHICSbusiness.industryintelligent 3D scannerGeneral EngineeringAtomic and Molecular Physics and OpticsROI localisation010201 computation theory & mathematics020201 artificial intelligence & image processingArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingadaptive pattern
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HDR-ARtiSt: High Dynamic Range Advanced Real-Time Imaging System

2012

International audience; This paper describes the HDR-ARtiSt hardware platform, a FPGA-based architecture that can produce a real- time high dynamic range video from successive image acquisition. The hardware platform is built around a standard low dynamic range (LDR) CMOS sensor and a Virtex 5 FPGA board. The CMOS sensor is a EV76C560 provided by e2v. This 1.3 Megapixel device offers novel pixel integration/readout modes and em- bedded image pre-processing capabilities including multiframe acquisition with various exposure times. Our approach consists of a hardware architecture with different algorithms: double exposure control during image capture, building of an HDR image by combining the…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer scienceHardware platformReal-time computingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processingVideo camera02 engineering and technologyTone mapping[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processinglaw.invention[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessinglawHistogram0202 electrical engineering electronic engineering information engineeringHigh dynamic rangeFPGA[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingHardware architectureCMOS sensorLiquid-crystal displayreal timePixelbusiness.industryDynamic range020207 software engineeringHigh Dynamic RangeFrame rate[SPI.TRON] Engineering Sciences [physics]/Electronics[ SPI.TRON ] Engineering Sciences [physics]/Electronicsimage processing[SPI.TRON]Engineering Sciences [physics]/ElectronicsIEEE020201 artificial intelligence & image processingbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingComputer hardware
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eISP, une architecture de calcul programmable pour l'amélioration d'images sur téléphone portable.

2009

4 pages; Today's smart phones, with their embedded high-resolution video sensors, require computing capacities that are too high to easily meet stringent silicon area and power consumption requirements (some one and a half square millimeters and half a watt) especially when programmable components are used. To develop such capacities, integrators still rely on dedicated low resolution video processing components, whose drawback is low flexibility. With this in mind, our paper presents eISP {--} a new, fully programmable Embedded Image Signal Processor architecture, now validated in {TSMC~65nm} technology to achieve a capacity of {16.8~GOPs} at {233~MHz}, for {1.5~mm$^2$} of silicon area and…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processinglow power[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingCMOS[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingeISPSIMDvideo pipeimage processing[INFO.INFO-MC]Computer Science [cs]/Mobile ComputingMulti-SIMD[INFO.INFO-MC] Computer Science [cs]/Mobile Computing[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[ INFO.INFO-MC ] Computer Science [cs]/Mobile Computing[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
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eISP: a Programmable Processing Architecture for Smart Phone Image Enhancement

2009

4 pages; Today's smart phones, with their embedded high-resolution video sensors, require computing capacities that are too high to easily meet stringent silicon area and power consumption requirements (some one and a half square millimeters and half a watt) especially when programmable components are used. To develop such capacities, integrators still rely on dedicated low resolution video processing components, whose drawback is low flexibility. With this in mind, our paper presents eISP {--} a new, fully programmable Embedded Image Signal Processor architecture, now validated in {TSMC 65nm} technology to achieve a capacity of {16.8 GOPs} at {233 MHz}, for {1.5 mm$^2$} of silicon area and…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processinglow power[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingCMOSdemosaïcking[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingeISPmm²SIMDimage processingvideo pipesmall siliconMulti-SIMDcomputing tilemilliwatt[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingsensordemosaicingTSMC 65nm[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
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Application of LSTM architectures for next frame forecasting in Sentinel-1 images time series

2020

L'analyse prédictive permet d'estimer les tendances des évènements futurs. De nos jours, les algorithmes Deep Learning permettent de faire de bonnes prédictions. Cependant, pour chaque type de problème donné, il est nécessaire de choisir l'architecture optimale. Dans cet article, les modèles Stack-LSTM, CNN-LSTM et ConvLSTM sont appliqués à une série temporelle d'images radar sentinel-1, le but étant de prédire la prochaine occurrence dans une séquence. Les résultats expérimentaux évalués à l'aide des indicateurs de performance tels que le RMSE et le MAE, le temps de traitement et l'index de similarité SSIM, montrent que chacune des trois architectures peut produire de bons résultats en fon…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]FOS: Computer and information sciencesApprentissage profondComputer Science - Machine LearningImage and Video Processing (eess.IV)[INFO.INFO-NE] Computer Science [cs]/Neural and Evolutionary Computing [cs.NE]PrévisionComputer Science - Neural and Evolutionary ComputingDeep Learning AlgorithmsPrédiction[INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE]Electrical Engineering and Systems Science - Image and Video ProcessingLand cover change[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Machine Learning (cs.LG)SARIMA[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV][INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]FOS: Electrical engineering electronic engineering information engineeringSatellite imagesNeural and Evolutionary Computing (cs.NE)LSTMPredictionForecastingImages satellitaires
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