Search results for "Telecommunication"

showing 10 items of 1769 documents

New Optimization and Security Approaches to Enhance the Smart Grid Performance and Reliability

2016

International audience; Nowadays, the Smart Grid (SG) is becoming smarter thanks to the integration of different information and communication technologies to enhance the reliability and efficiency of the power grid. However, several issues should be met to ensure high SG performance. Among these issues, we cite the problem of electric vehicles (EVs) integration into the SG to avoid electricity intermittence due to the important load that EVs can create. Another issue is the SG communication network security that can be attempted by malicious intruders in order to create damages and make the power grid instable. In this context, we propose at a first level a Bayesian game-theory model that …

[ INFO ] Computer Science [cs]Computer scienceDistributed computing02 engineering and technologyIntrusion detection system[INFO] Computer Science [cs]Bayesian gameGame TheoryRobustness (computer science)Bayesian Nash Equilibrium0202 electrical engineering electronic engineering information engineering[INFO]Computer Science [cs]Smart GridChallengesIntrusion Detection System020203 distributed computingbusiness.industry020206 networking & telecommunicationsTelecommunications networkSmart gridInformation and Communications TechnologyElectricitybusinessGame theoryElectric VehiclesComputer network
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Towards a methodology for semantic and context-aware mobile learning

2013

International audience; Internet and mobile devices open the way towards mobile learning (m-learning), offering new opportunities to extend learning beyond the traditional teacher-led classroom. M-learning is not only any form of teaching or studying that takes place when the user interacts with a mobile device. It is more than just using a mobile device to access resources and communicate with others. It should take account of the constant mobile situation of the learner. The challenge here is to exploit this continually changing situation with a system that can dynamically recognize and adapt educational resources and services to the "context" in which the learner operates (localization, …

[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR][INFO.INFO-WB] Computer Science [cs]/WebExploitComputer science[ INFO.INFO-IU ] Computer Science [cs]/Ubiquitous Computing[ INFO.INFO-WB ] Computer Science [cs]/WebContext (language use)02 engineering and technologycontextWorld Wide Webmobile learning[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing[INFO.INFO-MC]Computer Science [cs]/Mobile ComputingConstant (computer programming)semantic web[INFO.INFO-MC] Computer Science [cs]/Mobile Computing[ INFO.INFO-MC ] Computer Science [cs]/Mobile Computing0202 electrical engineering electronic engineering information engineeringMobile searchSemantic Webbusiness.industry[INFO.INFO-WB]Computer Science [cs]/Web[INFO.INFO-IU] Computer Science [cs]/Ubiquitous Computing020206 networking & telecommunicationsOpen learning[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]The Internet[INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]businessMobile device
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An Impulse Response Model for the 60 Ghz Channel Based on Spectral Techniques of alpha-stable Processes

2007

International audience; In order to make realistic simulations of the radio propagation mechanism in ultra-wide band channels, an appropriate model is needed. In this paper we propose a new technique to model the impulse response of the 60 Ghz channel. This new approach is based on the spectral analysis of alpha-stable processes. Our new model presents many advantages: firstly, the channel is characterized only by a one deterministic function (spectral density) in the place of four parameters. Secondly, the estimations procedure deals directly with the measured transfer functions which avoids loosing information in data pretreatment. Finally, an estimation of the spectral measure permits to…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer science02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingTransfer function[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0203 mechanical engineering[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]0202 electrical engineering electronic engineering information engineeringSpectral analysisTransient response[ MATH.MATH-ST ] Mathematics [math]/Statistics [math.ST]Impulse response[STAT.AP]Statistics [stat]/Applications [stat.AP]business.industry[ STAT.AP ] Statistics [stat]/Applications [stat.AP]Spectral density020302 automobile design & engineering020206 networking & telecommunications[STAT.TH]Statistics [stat]/Statistics Theory [stat.TH][ STAT.TH ] Statistics [stat]/Statistics Theory [stat.TH]Radio propagationTelecommunicationsbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingAlgorithmCommunication channel
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Multispectral Imaging using a Stereo Camera: Concept, Design and Assessment

2011

This paper proposes a one-shot six-channel multispectral color image acquisition system using a stereo camera and a pair of optical filters. The two filters from the best pair selected from among readily available filters such that they modify the sensitivities of the two cameras in such a way that they produce optimal estimation of spectral reflectance and/or color are placed in front of the two lenses of the stereo camera. The two images acquired from the stereo camera are then registered for pixel-to-pixel correspondence. The spectral reflectance and/or color at each pixel on the scene are estimated from the corresponding camera outputs in the two images. Both simulations and experiments…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer scienceMultispectral imageComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONlcsh:TK7800-836002 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing01 natural scienceslcsh:Telecommunicationlaw.inventionMultispectral pattern recognitionstereo camera010309 optics[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessinglawCamera auto-calibrationlcsh:TK5101-67200103 physical sciences0202 electrical engineering electronic engineering information engineeringmultispectral imagingComputer visionreflectance estimationPixelColor imagebusiness.industrylcsh:ElectronicsReflectivityLens (optics)020201 artificial intelligence & image processingArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing:Mathematics and natural science: 400::Information and communication science: 420::Simulation visualization signal processing image processing: 429 [VDP]Stereo cameraComputer stereo visionCamera resectioning
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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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Quadratic Objective Functions for Dichromatic Model Parameters Estimation

2017

International audience; In this paper, we present a novel method to estimate dichromatic model parameters from a single color image. Estimation of reflectance, shading and specularity has many applications such as shape recovery, specularity removal and facilitates classical image processing and computer vision tasks such as segmentation or classification. Our method is based on two successive and independent constrained quadratic programming steps to recover the parameters of the model. Compared to recent methods, our approach has the advantage to transform a complex inverse problem into two parralelizable optimization steps that are much easier to solve. We have compared our method with r…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingLinear programmingColor imagebusiness.industry[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020206 networking & telecommunicationsImage processing02 engineering and technologyInverse problem[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Quadratic equation[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Specularity[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingRobustness (computer science)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer visionQuadratic programmingArtificial intelligencebusinessAlgorithmMathematics
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A new minimum trees-based approach for shape matching with improved time computing : application to graphical symbols recognition

2010

Recently we have developed a model for shape description and matching. Based on minimum spanning trees construction and specifics stages like the mixture, it seems to have many desirable properties. Recognition invariance in front shift, rotated and noisy shape was checked through median scale tests related to GREC symbol reference database. Even if extracting the topology of a shape by mapping the shortest path connecting all the pixels seems to be powerful, the construction of graph induces an expensive algorithmic cost. In this article we discuss on the ways to reduce time computing. An alternative solution based on image compression concepts is provided and evaluated. The model no longe…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingMatching (graph theory)[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer scienceFeature extractionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingMinimum spanning tree[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingActive shape model0202 electrical engineering electronic engineering information engineeringDiscrete cosine transformComputingMilieux_MISCELLANEOUS[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingSpanning treebusiness.industry020206 networking & telecommunicationsPattern recognitionGraphShortest path problemGraph (abstract data type)020201 artificial intelligence & image processingArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingImage compression
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Scene-based noise reduction on a smart camera

2012

International audience; Raw output data from CMOS image sensors tends to exhibit significant noise called Fixed-Pattern Noise (FPN) due to on-die variations between pixel photodetectors. FPN is often corrected by subtracting its value, estimated through calibration, from the sensor's raw signal. This paper introduces an on-line scene-based technique for an improved FPN compensation which does not rely on calibration, and hence is more robust to the dynamic changes in the FPN which may occur slowly over time. Development has been done with a special emphasis on real-time hardware implementation on a FPGA-based smart camera. Experimental results on different scenes are depicted showing that t…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer scienceNoise reductionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing01 natural sciencesSignalCompensation (engineering)010309 optics[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0103 physical sciences0202 electrical engineering electronic engineering information engineeringComputer visionSmart cameraImage sensor[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingPixelNoise (signal processing)business.industry020208 electrical & electronic engineeringEmphasis (telecommunications)Artificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Noise estimation from digital step-model signal

2013

International audience; This paper addresses the noise estimation in the digital domain and proposes a noise estimator based on the step signal model. It is efficient for any distribution of noise because it does not rely only on the smallest amplitudes in the signal or image. The proposed approach uses polarized/directional derivatives and a nonlinear combination of these derivatives to estimate the noise distribution (e.g., Gaussian, Poisson, speckle, etc.). The moments of this measured distribution can be computed and are also calculated theoretically on the basis of noise distribution models. The 1D performances are detailed, and as our work is mostly dedicated to image processing, a 2D…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processingstep model02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingCCD sensornoise distributionsymbols.namesake[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processingdigital signalsalt and pepper noiseStatistics0202 electrical engineering electronic engineering information engineeringMedian filterImage noisePoisson noiseValue noiseNoise estimationMathematics[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingedge modelmultiplicative noiseNoise measurementNoise (signal processing)020206 networking & telecommunicationsComputer Graphics and Computer-Aided DesignNoise floorGaussian white noiseGradient noiseimpulse noiseGaussian noisenonlinear modelsymbols020201 artificial intelligence & image processingnoise estimatorAlgorithm[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingSoftware
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Incorporating depth information into few-shot semantic segmentation

2021

International audience; Few-shot segmentation presents a significant challengefor semantic scene understanding under limited supervision.Namely, this task targets at generalizing the segmentationability of the model to new categories given a few samples.In order to obtain complete scene information, we extend theRGB-centric methods to take advantage of complementary depthinformation. In this paper, we propose a two-stream deep neuralnetwork based on metric learning. Our method, known as RDNet,learns class-specific prototype representations within RGB anddepth embedding spaces, respectively. The learned prototypesprovide effective semantic guidance on the corresponding RGBand depth query ima…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]Artificial neural networkComputer sciencebusiness.industry[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020206 networking & telecommunications02 engineering and technologyImage segmentationSemanticsVisualization[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI][INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingMetric (mathematics)0202 electrical engineering electronic engineering information engineeringEmbeddingRGB color modelSegmentationComputer visionArtificial intelligencebusiness
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