Search results for " Pattern recognition"

showing 10 items of 1050 documents

Restricted compositions and permutations: from old to new Gray codes

2011

Any Gray code for a set of combinatorial objects defines a total order relation on this set: x is less than y if and only if y occurs after x in the Gray code list. Let @? denote the order relation induced by the classical Gray code for the product set (the natural extension of the Binary Reflected Gray Code to k-ary tuples). The restriction of @? to the set of compositions and bounded compositions gives known Gray codes for those sets. Here we show that @? restricted to the set of bounded compositions of an interval yields still a Gray code. An n-composition of an interval is an n-tuple of integers whose sum lies between two integers; and the set of bounded n-compositions of an interval si…

0102 computer and information sciences02 engineering and technologyInterval (mathematics)[ MATH.MATH-CO ] Mathematics [math]/Combinatorics [math.CO]01 natural sciencesTheoretical Computer ScienceCombinatoricsGray codePermutationsymbols.namesakeInteger020204 information systems[MATH.MATH-CO]Mathematics [math]/Combinatorics [math.CO]0202 electrical engineering electronic engineering information engineeringComputingMilieux_MISCELLANEOUSMathematicsDiscrete mathematicsExtension (predicate logic)Composition (combinatorics)Cartesian productComputer Science Applications010201 computation theory & mathematicsComputer Science::Computer Vision and Pattern RecognitionBounded functionSignal ProcessingsymbolsInformation Systems
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Promotion et Développement d'un Master Erasmus Mundus - L'Exemple du VIBOT

2011

Cet article decrit l’offre de formation a l’internationale proposee au Centre Universitaire Condorcet du Creusot (Universite de Bourgogne) dans le domaine de la vision par ordinateur et de la robotique. Il presente l’organisation particuliere de ces formations et les actions de support mises en place pour en assurer la perennite.

010201 computation theory & mathematics05 social sciences050301 education[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]0102 computer and information sciences16. Peace & justice[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]0503 education01 natural sciences
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Mass calibration of the energy axis in ToF- E elastic recoil detection analysis

2016

We report on procedures that we have developed to mass-calibrate the energy axis of ToF-E histograms in elastic recoil detection analysis. The obtained calibration parameters allow one to transform the ToF-E histogram into a calibrated ToF-M histogram.

010302 applied physicsPhysicsNuclear and High Energy Physicsta114Physics::Instrumentation and DetectorsPhysics::Medical PhysicsAstrophysics::Instrumentation and Methods for AstrophysicsERD02 engineering and technology021001 nanoscience & nanotechnology01 natural sciencesNuclear physicsElastic recoil detectionComputer Science::Computer Vision and Pattern RecognitionHistogramelastic recoil detection analysis0103 physical sciencesCalibrationmass calibrationToF-ENuclear Experiment0210 nano-technologyInstrumentationEnergy (signal processing)Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms
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Estimating Missing Information by Cluster Analysis and Normalized Convolution

2018

International audience; Smart city deals with the improvement of their citizens' quality of life. Numerous ad-hoc sensors need to be deployed to know humans' activities as well as the conditions in which these actions take place. Even if these sensors are cheaper and cheaper, their installation and maintenance cost increases rapidly with their number. We propose a methodology to limit the number of sensors to deploy by using a standard clustering technique and the normalized convolution to estimate environmental information whereas sensors are actually missing. In spite of its simplicity, our methodology lets us provide accurate assesses.

010504 meteorology & atmospheric sciencesComputer sciencemedia_common.quotation_subjectReal-time computingEnergy Engineering and Power Technology02 engineering and technologyIterative reconstructionsmart city dealsCluster (spacecraft)01 natural sciencesIndustrial and Manufacturing Engineeringnormalized convolutionstandard clustering technique[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]ConvolutionArtificial IntelligenceSmart city11. Sustainability0202 electrical engineering electronic engineering information engineeringLimit (mathematics)SimplicityCluster analysisInstrumentationad-hoc sensors0105 earth and related environmental sciencesmedia_commonSettore INF/01 - InformaticaRenewable Energy Sustainability and the EnvironmentComputer Science Applications1707 Computer Vision and Pattern Recognitionenvironmental informationmissing informationComputer Networks and CommunicationKernel (image processing)020201 artificial intelligence & image processingcluster analysis2018 IEEE 4th International Forum on Research and Technology for Society and Industry (RTSI)
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Exploiting Maximum Entropy method and ASTER data for assessing debris flow and debris slide susceptibility for the Giampilieri catchment (north-easte…

2016

This study aims at evaluating the performance of the Maximum Entropy method in assessing landslide susceptibility, exploiting topographic and multispectral remote sensing predictors. We selected the catchment of the Giampilieri stream, which is located in the north-eastern sector of Sicily (southern Italy), as test site. On 1 October 2009, a storm rainfall triggered in this area hundreds of debris flow/avalanche phenomena causing extensive economical damage and loss of life. Within this area a presence-only-based statistical method was applied to obtain susceptibility models capable of distinguishing future activation sites of debris flow and debris slide, which where the main source of fai…

010504 meteorology & atmospheric sciencesGeography Planning and DevelopmentMultispectral imageLandslideLand cover010502 geochemistry & geophysics01 natural sciencesDebrisMultispectral pattern recognitionDebris flowAdvanced Spaceborne Thermal Emission and Reflection RadiometerEarth and Planetary Sciences (miscellaneous)Digital elevation modelGeology0105 earth and related environmental sciencesEarth-Surface ProcessesRemote sensingEarth Surface Processes and Landforms
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In situ Phenotyping of Grapevine Root System Architecture by 2D or 3D Imaging: Advantages and Limits of Three Cultivation Methods

2021

International audience; The root system plays an essential role in the development and physiology of the plant, as well as in its response to various stresses. However, it is often insufficiently studied, mainly because it is difficult to visualize. For grapevine, a plant of major economic interest, there is a growing need to study the root system, in particular to assess its resistance to biotic and abiotic stresses, understand the decline that may affect it, and identify new ecofriendly production systems. In this context, we have evaluated and compared three distinct growing methods (hydroponics, plane, and cylindric rhizotrons) in order to describe relevant architectural root traits of …

0106 biological sciences0301 basic medicineRoot (linguistics)phenotypingContext (language use)Root systemPlant ScienceBiologyrhizotron01 natural sciencesSkeletonizationSB1-111003 medical and health sciencesCutting[SDV.SA.STA]Life Sciences [q-bio]/Agricultural sciences/Sciences and technics of agricultureMethods2. Zero hungerroot system architectureNeutron tomographyRhizotronPlant culture[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]15. Life on landHydroponicsgrapevine2D/3D imaging030104 developmental biologyroot traitsneutron tomographyBiological system010606 plant biology & botanyFrontiers in Plant Science
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Benchmark database for fine-grained image classification of benthic macroinvertebrates

2018

Managing the water quality of freshwaters is a crucial task worldwide. One of the most used methods to biomonitor water quality is to sample benthic macroinvertebrate communities, in particular to examine the presence and proportion of certain species. This paper presents a benchmark database for automatic visual classification methods to evaluate their ability for distinguishing visually similar categories of aquatic macroinvertebrate taxa. We make publicly available a new database, containing 64 types of freshwater macroinvertebrates, ranging in number of images per category from 7 to 577. The database is divided into three datasets, varying in number of categories (64, 29, and 9 categori…

0106 biological sciencesComputer scienceta1172Sample (statistics)monitorointi02 engineering and technologyneuroverkot01 natural sciencesConvolutional neural network0202 electrical engineering electronic engineering information engineeringkonenäköfine-grained classification14. Life underwaterFine-grained classificationInvertebrateta113ta112Contextual image classificationbusiness.industry010604 marine biology & hydrobiologyDeep learningConvolutional Neural NetworksBenchmark databasedeep learningPattern recognitionDeep learningselkärangattomatvedenlaatu6. Clean waterkoneoppiminenBenthic zoneBenthic macroinvertebratesbiomonitoringSignal ProcessingBiomonitoringta1181lajinmääritys020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionArtificial intelligenceWater qualitybusinessbenthic macroinvertebrates
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Temperate Fish Detection and Classification: a Deep Learning based Approach

2021

A wide range of applications in marine ecology extensively uses underwater cameras. Still, to efficiently process the vast amount of data generated, we need to develop tools that can automatically detect and recognize species captured on film. Classifying fish species from videos and images in natural environments can be challenging because of noise and variation in illumination and the surrounding habitat. In this paper, we propose a two-step deep learning approach for the detection and classification of temperate fishes without pre-filtering. The first step is to detect each single fish in an image, independent of species and sex. For this purpose, we employ the You Only Look Once (YOLO) …

0106 biological sciencesFOS: Computer and information sciencesComputer Science - Machine LearningComputer scienceComputer Vision and Pattern Recognition (cs.CV)Computer Science - Computer Vision and Pattern Recognition010603 evolutionary biology01 natural sciencesConvolutional neural networkVDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420Machine Learning (cs.LG)Artificial IntelligenceClassifier (linguistics)FOS: Electrical engineering electronic engineering information engineeringbusiness.industry010604 marine biology & hydrobiologyDeep learningImage and Video Processing (eess.IV)Process (computing)Pattern recognitionElectrical Engineering and Systems Science - Image and Video ProcessingObject detectionA priori and a posterioriNoise (video)Artificial intelligenceTransfer of learningbusiness
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A segmentation algorithm for noisy images

2005

International audience; This paper presents a segmentation algorithm for gray-level images and addresses issues related to its performance on noisy images. It formulates an image segmentation problem as a partition of a weighted image neighborhood hypergraph. To overcome the computational difficulty of directly solving this problem, a multilevel hypergraph partitioning has been used. To evaluate the algorithm, we have studied how noise affects the performance of the algorithm. The alpha-stable noise is considered and its effects on the algorithm are studied. Key words : graph, hypergraph, neighborhood hypergraph, multilevel hypergraph partitioning, image segmentation and noise removal.

020203 distributed computingHypergraphMathematics::Combinatorics[ INFO ] Computer Science [cs]Computer sciencebusiness.industrySegmentation-based object categorizationComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-space segmentationImage processing02 engineering and technologyImage segmentation[INFO] Computer Science [cs]020202 computer hardware & architectureComputer Science::Computer Vision and Pattern Recognition0202 electrical engineering electronic engineering information engineeringGraph (abstract data type)SegmentationComputer vision[INFO]Computer Science [cs]Artificial intelligencebusinessAlgorithmMathematicsofComputing_DISCRETEMATHEMATICS
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Flow measurement using circular portable flume

2018

Abstract The circular portable flume is a simple device to measure discharge in circular drainage networks. Since the unit can be easily installed and removed, it is helpful in water distribution measurement and management. First in this paper the available studies are reviewed for highlighting the effect of both the contraction ratio and the flume slope on the stage-discharge relationship. Then the Buckingham's Theorem of the dimensional analysis and the self-similarity theory are used to deduce the stage-discharge curve of the circular flume. The new theoretical stage-discharge equation is calibrated by the literature available experimental data and those obtained in this experimental inv…

0208 environmental biotechnology02 engineering and technology01 natural sciencesMeasure (mathematics)Flow measurement010309 optics0103 physical sciencesRange (statistics)Portable flumeStage-discharge curveSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliElectrical and Electronic EngineeringBuckingham's theoremContraction (operator theory)Contraction ratioInstrumentationDrainage networkExperimental dataComputer Science Applications1707 Computer Vision and Pattern RecognitionMechanics020801 environmental engineeringComputer Science ApplicationsFlumeFlow measurementDistribution (mathematics)Circular flumeModeling and SimulationGeology
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