Search results for "soft"

showing 10 items of 9809 documents

Architectural Reconstruction of 3D Building Objects through Semantic Knowledge Management

2010

International audience; This paper presents an ongoing research which aims at combining geometrical analysis of point clouds and semantic rules to detect 3D building objects. Firstly by applying a previous semantic formalization investigation, we propose a classification of related knowledge as definition, partial knowledge and ambiguous knowledge to facilitate the understanding and design. Secondly an empirical implementation is conducted on a simplified building prototype complying with the IFC standard. The generation of empirical knowledge rules is revealed and semantic scopes are addressed both in the bottom up manner along the line of geometry --> topology --> semantic, and a vice ver…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]cognitionComputer science02 engineering and technologySemanticscomputer.software_genreSocial Semantic Webformal[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Semantic similaritySemantic computing0202 electrical engineering electronic engineering information engineering[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB][ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]Semantic WebInformation retrieval[INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]Semantic Web Rule Languagebusiness.industryepistemology020207 software engineeringknowledge management[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB]Semantic gridsemanticSemantic technology020201 artificial intelligence & image processingData miningbusinesscomputer
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Automated uncertainty quantification analysis using a system model and data

2015

International audience; Understanding the sources of, and quantifying the magnitude of, uncertainty can improve decision-making and, thereby, make manufacturing systems more efficient. Achieving this goal requires knowledge in two separate domains: data science and manufacturing. In this paper, we focus on quantifying uncertainty, usually called uncertainty quantification (UQ). More specifically, we propose a methodology to perform UQ automatically using Bayesian networks (BN) constructed from three types of sources: a descriptive system model, physics-based mathematical models, and data. The system model is a high-level model describing the system and its parameters; we develop this model …

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]generic modeling environment[SPI] Engineering Sciences [physics]Computer scienceuncertainty quantificationMachine learningcomputer.software_genre01 natural sciencesData modelingSystem model[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]010104 statistics & probability03 medical and health sciences[SPI]Engineering Sciences [physics][ SPI ] Engineering Sciences [physics]Sensitivity analysis0101 mathematicsUncertainty quantification[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]030304 developmental biologyautomation0303 health sciencesMathematical modelbusiness.industryConditional probabilityBayesian networkmeta-modelMetamodelingBayesian networkProbability distributionData miningArtificial intelligencebusinesscomputer
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Advanced 3D movement analysis algorithms for robust functional capacity assessment.

2017

SummaryObjectives: We developed a novel system for in home functional capacities assessment in frail older adults by analyzing the Timed Up and Go movements. This system aims to follow the older people evolution, potentially allowing a forward detection of motor decompensation in order to trigger the implementation of rehabilitation. However, the pre-experimentations conducted on the ground, in different environments, revealed some problems which were related to KinectTM operation. Hence, the aim of this actual study is to develop methods to resolve these problems.Methods: Using the KinectTM sensor, we analyze the Timed Up and Go test movements by measuring nine spatio-temporal parameters, …

[INFO.INFO-AR]Computer Science [cs]/Hardware Architecture [cs.AR]Computer science02 engineering and technologyTimed Up and Go testcomputer.software_genreCorrelation0302 clinical medicineHealth Information ManagementMICROSOFT KINECT0202 electrical engineering electronic engineering information engineering[INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO][ SDV.IB ] Life Sciences [q-bio]/Bioengineeringsitting posture recognition[ INFO.INFO-RB ] Computer Science [cs]/Robotics [cs.RO]FALLSVideo processingPatient self-care home care and e-healthComputer Science Applications3D real-time video processing020201 artificial intelligence & image processing[SDV.IB]Life Sciences [q-bio]/BioengineeringAlgorithmsClinical testsCapacity assessmentGO TESTskin detectionFrail ElderlyMovementFrail Older AdultsPostureHealth InformaticsMachine learning03 medical and health sciencesRobustness (computer science)[ SDV.MHEP ] Life Sciences [q-bio]/Human health and pathologyclinical informaticsHumansVALIDITYOLDER-ADULTSSimulationAgedMonitoring Physiologicbusiness.industryMovement analysisMOTOR STRATEGIESArtificial intelligencebusinesscomputer030217 neurology & neurosurgery[SDV.MHEP]Life Sciences [q-bio]/Human health and pathologyApplied clinical informatics
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A Mobile Computing Framework for Pervasive Adaptive Platforms

2012

International audience; Ubiquitous computing is now the new computing trend, such systems that interact with their environment require self-adaptability. Bioinspiration is a natural candidate to provide the capability to handle complex and changing scenarios. This paper presents a programming framework dedicated to pervasive platforms programming. This bioinspired and agentoriented framework has been developed within the frame of the PERPLEXUS European project that is intended to provide support for bioinspiration-driven system adaptability. This framework enables the platform to adapt itself to application requirements at high-level while using hardware acceleration at node level. The resu…

[INFO.INFO-AR]Computer Science [cs]/Hardware Architecture [cs.AR]Context-aware pervasive systemsUbiquitous computingArticle SubjectComputer Networks and CommunicationsComputer scienceDistributed computingmedia_common.quotation_subjectMobile computing02 engineering and technologycomputer.software_genreAdaptabilitylcsh:QA75.5-76.950202 electrical engineering electronic engineering information engineeringAdaptation (computer science)media_commonbusiness.industryFrame (networking)General Engineering020206 networking & telecommunicationsSoftware frameworkEmbedded systemHardware accelerationRobot020201 artificial intelligence & image processinglcsh:Electronic computers. Computer sciencebusinesscomputer
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Embedded multi-spectral image processing for real-time medical application

2016

International audience; The newly introduced Kubelka-Munk Genetic Algorithm (KMGA) is a promising technique for the assessment of skin lesions from multi-spectral images. Using five skin parameter maps such as concentration or epidermis/dermis thickness, this method combines the Kubelka-Munk Light-Tissue interaction model and Genetic Algorithm optimization process to produce a quantitative measure of cutaneous tissue. Up to the present, variant improved KMGA implementations have been successfully realized using the recent parallel computing techniques. However, all these achievements are based on the multi-core CPUs. This results in a quite high cost and low practicability for the hardware …

[INFO.INFO-AR]Computer Science [cs]/Hardware Architecture [cs.AR]Digital signal processorSource code[ INFO ] Computer Science [cs]Computer sciencemedia_common.quotation_subject[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]Image processing02 engineering and technologyARCHITECTURESLight-Tissue InteractionGenetic algorithm0202 electrical engineering electronic engineering information engineering[INFO]Computer Science [cs]Embedded SystemField-programmable gate arrayFPGA[ INFO.INFO-DS ] Computer Science [cs]/Data Structures and Algorithms [cs.DS]media_commonFlexibility (engineering)Multi-spectral image processingGenetic AlgorithmHigh-Level Synthesis FPGA IMPLEMENTATIONbusiness.industryProcess (computing)020206 networking & telecommunicationsTransplantationMODELComputer engineeringHardware and ArchitectureEmbedded system020201 artificial intelligence & image processing[ INFO.INFO-AR ] Computer Science [cs]/Hardware Architecture [cs.AR]businessHigh-Level SynthesisSoftware
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Palmprint and face score level fusion: hardware implementation of a contactless small sample biometric system

2011

Including multiple sources of information in personal identity recognition and verification gives the opportunity to greatly improve performance. We propose a contactless biometric system that combines two modalities: palmprint and face. Hardware implementations are proposed on the Texas Instrument Digital Signal Processor and Xilinx Field-Programmable Gate Array (FPGA) platforms. The algorithmic chain consists of a preprocessing (which includes palm extraction from hand images), Gabor feature extraction, comparison by Hamming distance, and score fusion. Fusion possibilities are discussed and tested first using a bimodal database of 130 subjects that we designed (uB database), and then two …

[INFO.INFO-AR]Computer Science [cs]/Hardware Architecture [cs.AR]Image fusion[INFO.INFO-AR] Computer Science [cs]/Hardware Architecture [cs.AR]BiometricsComputer sciencebusiness.industryFeature extractionGeneral EngineeringWord error rate020207 software engineeringImage processing02 engineering and technologyFacial recognition systemAtomic and Molecular Physics and OpticsMultimodal biometricsPattern recognition (psychology)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer visionArtificial intelligence[ INFO.INFO-AR ] Computer Science [cs]/Hardware Architecture [cs.AR]businessComputer hardware
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LDR Image to HDR Image Mapping with Overexposure Preprocessing

2013

International audience; Due to the growing popularity of High Dynamic Range (HDR) images and HDR displays, a large amount of existing Low Dynamic Range (LDR) images are required to be converted to HDR format to benefit HDR advantages, which give rise to some LDR to HDR algorithms. Most of these algorithms especially tackle overexposed areas during expanding, which is the potential to make the image quality worse than that before processing and introduces artifacts. To dispel these problems, we . present a new,LDR to HDR approach, unlike the existing techniques, it focuses on avoiding sophisticated treatment to overexposed areas in dynamic range expansion step. Based on a separating principl…

[INFO.INFO-AR]Computer Science [cs]/Hardware Architecture [cs.AR]Image qualityComputer scienceImage mapPrincipal component analysisComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONHDR02 engineering and technologyImage (mathematics)Highlight removal0202 electrical engineering electronic engineering information engineeringPreprocessorComputer visionElectrical and Electronic EngineeringComputingMilieux_MISCELLANEOUSHigh dynamic rangeExposurebusiness.industryDynamic rangeApplied MathematicsImage quality metric020207 software engineeringComputer Graphics and Computer-Aided DesignOverexposed areaSignal ProcessingMetric (mathematics)020201 artificial intelligence & image processing[ INFO.INFO-AR ] Computer Science [cs]/Hardware Architecture [cs.AR]Artificial intelligencebusinessIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
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Design of a Real-time face detection parallel architecture using High-Level Synthesis

2008

Abstract We describe a High-Level Synthesis implementation of a parallel architecture for face detection. The chosen face detection method is the well-known Convolutional Face Finder (CFF) algorithm, which consists of a pipeline of convolution operations. We rely on dataflow modelling of the algorithm and we use a high-level synthesis tool in order to specify the local dataflows of our Processing Element (PE), by describing in C language inter-PE communication, fine scheduling of the successive convolutions, and memory distribution and bandwidth. Using this approach, we explore several implementation alternatives in order to find a compromise between processing speed and area of the PE. We …

[INFO.INFO-AR]Computer Science [cs]/Hardware Architecture [cs.AR][INFO.INFO-AR] Computer Science [cs]/Hardware Architecture [cs.AR]General Computer ScienceVideo Graphics ArrayComputer scienceDataflowlcsh:Electronicslcsh:TK7800-8360020207 software engineering02 engineering and technologyParallel computing020202 computer hardware & architectureConvolutionScheduling (computing)Control and Systems EngineeringHigh-level synthesis0202 electrical engineering electronic engineering information engineeringParallel architecture[ INFO.INFO-AR ] Computer Science [cs]/Hardware Architecture [cs.AR]ArchitectureFace detectionComputingMilieux_MISCELLANEOUSComputer Science(all)
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PROCEDE DE PRE-DISTORSION NUMERIQUE D’UN SIGNAL ET REPETEUR DE TELECOMMUNICATION INTEGRANT UN FILTRE A REPONSE IMPULSIONNELLE FINIE POUR METTRE EN OE…

2013

L'invention concerne un procédé de pré-distorsion numérique d'un signal de télécommunication traité dans un circuit électronique 100 intégrant un filtre à réponse impulsionnelle finie 321. Ce procédé consiste successivement: - à identifier, à la sortie du circuit 100, les paramètres de distorsions de phase et/ou d'amplitude du signal en fonction de la fréquence, - à partir des susdits paramètres de distorsions relevés, à générer, par un algorithme basé sur une interpolation, des coefficients permettant d'effectuer dans ledit filtre 321, des prédistorsions du signal numérique destinées à engendrer une précorrection des susdites distorsions, - à transférer lesdits coefficients de pré-distorsi…

[INFO.INFO-AR]Computer Science [cs]/Hardware Architecture [cs.AR][SPI.OTHER]Engineering Sciences [physics]/Other[INFO.INFO-AR] Computer Science [cs]/Hardware Architecture [cs.AR][ SPI.OTHER ] Engineering Sciences [physics]/Other[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing[INFO.INFO-SI]Computer Science [cs]/Social and Information Networks [cs.SI]Prédistorsion numérique[ INFO.INFO-ES ] Computer Science [cs]/Embedded SystemsRépéteurs[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing[INFO.INFO-MS]Computer Science [cs]/Mathematical Software [cs.MS][ INFO.INFO-SI ] Computer Science [cs]/Social and Information Networks [cs.SI][SPI.OTHER] Engineering Sciences [physics]/Other[INFO.INFO-SI] Computer Science [cs]/Social and Information Networks [cs.SI]Spline[SPI.TRON] Engineering Sciences [physics]/Electronics[INFO.INFO-ES] Computer Science [cs]/Embedded Systems[ SPI.TRON ] Engineering Sciences [physics]/Electronics[SPI.TRON]Engineering Sciences [physics]/Electronics[ INFO.INFO-MS ] Computer Science [cs]/Mathematical Software [cs.MS][INFO.INFO-MS] Computer Science [cs]/Mathematical Software [cs.MS]FIR filters[INFO.INFO-ES]Computer Science [cs]/Embedded Systems[ INFO.INFO-AR ] Computer Science [cs]/Hardware Architecture [cs.AR][SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingFpga
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Scheduling independent stochastic tasks on heterogeneous cloud platforms

2019

International audience; This work introduces scheduling strategies to maximize the expected number of independent tasks that can be executed on a cloud platform within a given budget and under a deadline constraint. The cloud platform is composed of several types of virtual machines (VMs), where each type has a unitexecution cost that depends upon its characteristics. The amount of budget spent during the execution of a task on a given VM is the product of its execution length by the unit execution cost of that VM. The execution lengths of tasks follow a variety of standard probability distributions (exponential, uniform, halfnormal, etc.), which is known beforehand and whose mean and stand…

[INFO.INFO-CC]Computer Science [cs]/Computational Complexity [cs.CC]020203 distributed computingComputer scienceStochastic processbusiness.industryDistributed computing[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]Processor schedulingCloud computing02 engineering and technologycomputer.software_genreScheduling (computing)Virtual machine0202 electrical engineering electronic engineering information engineeringTask analysisProbability distribution020201 artificial intelligence & image processing[INFO]Computer Science [cs][INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]InterruptHeuristicsbusinesscomputer
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