Search results for "DISTANCE"

showing 10 items of 1009 documents

Hybrid blind robust image watermarking technique based on DFT-DCT and Arnold transform

2018

In this paper, a robust blind image watermarking method is proposed for copyright protection of digital images. This hybrid method relies on combining two well-known transforms that are the discrete Fourier transform (DFT) and the discrete cosine transform (DCT). The motivation behind this combination is to enhance the imperceptibility and the robustness. The imperceptibility requirement is achieved by using magnitudes of DFT coefficients while the robustness improvement is ensured by applying DCT to the DFT coefficients magnitude. The watermark is embedded by modifying the coefficients of the middle band of the DCT using a secret key. The security of the proposed method is enhanced by appl…

FOS: Computer and information sciencesComputer Science - Cryptography and SecurityComputer Networks and CommunicationsComputer scienceMultiple Watermarking02 engineering and technologyDiscrete Fourier transformImage (mathematics)Digital imageDiscrete Fourier transform (DFT)SchemeRobustness (computer science)Quantization0202 electrical engineering electronic engineering information engineeringMedia TechnologyDiscrete cosine transformHybrid method[INFO]Computer Science [cs]Digital watermarkingDiscrete cosine transform (DCT)DistanceImage watermarking020207 software engineeringWatermarkMultimedia (cs.MM)Hardware and ArchitectureMedical ImagesEmbedding020201 artificial intelligence & image processingArnold transformWavelet DomainSvdCryptography and Security (cs.CR)AlgorithmCopyright protectionSoftwareComputer Science - Multimedia
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Emulation as an Accurate Alternative to Interpolation in Sampling Radiative Transfer Codes

2018

Computationally expensive radiative transfer models (RTMs) are widely used to realistically reproduce the light interaction with the earth surface and atmosphere. Because these models take long processing time, the common practice is to first generate a sparse look-up table (LUT) and then make use of interpolation methods to sample the multidimensional LUT input variable space. However, the question arise whether common interpolation methodsperform most accurate. As an alternative to interpolation, this paper proposes to use emulation, i.e., approximating the RTM output by means of the statistical learning. Two experiments were conducted to assess the accuracy in delivering spectral outputs…

FOS: Computer and information sciencesComputer Science - Machine LearningAtmospheric Science010504 meteorology & atmospheric sciencesComputer science0211 other engineering and technologiesFOS: Physical sciences02 engineering and technologyStatistics - Applications01 natural sciencesArticleMachine Learning (cs.LG)Sampling (signal processing)KrigingInverse distance weightingApplications (stat.AP)Computers in Earth Sciences021101 geological & geomatics engineering0105 earth and related environmental sciencesEmulationArtificial neural networkMODTRANComputational Physics (physics.comp-ph)Physics - Atmospheric and Oceanic PhysicsAtmospheric and Oceanic Physics (physics.ao-ph)Lookup tablePhysics - Computational PhysicsAlgorithmInterpolationIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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Nonlinear Cook distance for Anomalous Change Detection

2020

In this work we propose a method to find anomalous changes in remote sensing images based on the chronochrome approach. A regressor between images is used to discover the most {\em influential points} in the observed data. Typically, the pixels with largest residuals are decided to be anomalous changes. In order to find the anomalous pixels we consider the Cook distance and propose its nonlinear extension using random Fourier features as an efficient nonlinear measure of impact. Good empirical performance is shown over different multispectral images both visually and quantitatively evaluated with ROC curves.

FOS: Computer and information sciencesComputer Science - Machine LearningComputer scienceComputer Vision and Pattern Recognition (cs.CV)Multispectral imageComputer Science - Computer Vision and Pattern Recognition0211 other engineering and technologies02 engineering and technologyMeasure (mathematics)Machine Learning (cs.LG)Kernel (linear algebra)symbols.namesake0502 economics and businessCook's distance021101 geological & geomatics engineering050208 financePixelbusiness.industry05 social sciencesPattern recognitionNonlinear systemFourier transformKernel (image processing)Computer Science::Computer Vision and Pattern RecognitionsymbolsArtificial intelligencebusinessChange detection
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Deep Learning Based Cardiac MRI Segmentation: Do We Need Experts?

2021

Deep learning methods are the de facto solutions to a multitude of medical image analysis tasks. Cardiac MRI segmentation is one such application, which, like many others, requires a large number of annotated data so that a trained network can generalize well. Unfortunately, the process of having a large number of manually curated images by medical experts is both slow and utterly expensive. In this paper, we set out to explore whether expert knowledge is a strict requirement for the creation of annotated data sets on which machine learning can successfully be trained. To do so, we gauged the performance of three segmentation models, namely U-Net, Attention U-Net, and ENet, trained with dif…

FOS: Computer and information sciencesComputer Science - Machine LearningComputer scienceProcess (engineering)GeneralizationIndustrial engineering. Management engineeringComputer Vision and Pattern Recognition (cs.CV)Computer Science - Computer Vision and Pattern Recognitionheartannotated data setT55.4-60.8Machine learningcomputer.software_genre030218 nuclear medicine & medical imagingTheoretical Computer ScienceMachine Learning (cs.LG)Set (abstract data type)03 medical and health sciences0302 clinical medicineFOS: Electrical engineering electronic engineering information engineeringSegmentationNumerical AnalysisArtificial neural networkbusiness.industryDeep learningsegmentationImage and Video Processing (eess.IV)deep learningQA75.5-76.95Electrical Engineering and Systems Science - Image and Video ProcessingComputational MathematicsHausdorff distanceComputational Theory and MathematicsIndex (publishing)Electronic computers. Computer scienceArtificial intelligencebusinesscomputer030217 neurology & neurosurgeryMRI
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PerceptNet: A Human Visual System Inspired Neural Network for Estimating Perceptual Distance

2019

Traditionally, the vision community has devised algorithms to estimate the distance between an original image and images that have been subject to perturbations. Inspiration was usually taken from the human visual perceptual system and how the system processes different perturbations in order to replicate to what extent it determines our ability to judge image quality. While recent works have presented deep neural networks trained to predict human perceptual quality, very few borrow any intuitions from the human visual system. To address this, we present PerceptNet, a convolutional neural network where the architecture has been chosen to reflect the structure and various stages in the human…

FOS: Computer and information sciencesComputer Science - Machine LearningVisual perceptionComputer scienceImage qualitymedia_common.quotation_subjectFeature extractionMachine Learning (stat.ML)02 engineering and technology01 natural sciencesConvolutional neural networkhuman visual systemMachine Learning (cs.LG)010309 opticsStatistics - Machine LearningPerception0103 physical sciences0202 electrical engineering electronic engineering information engineeringFOS: Electrical engineering electronic engineering information engineeringperceptual distancemedia_commonArtificial neural networkbusiness.industryDeep learningImage and Video Processing (eess.IV)Pattern recognitionElectrical Engineering and Systems Science - Image and Video Processingneural networksHuman visual system model020201 artificial intelligence & image processingArtificial intelligencebusiness
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Isometric Words Based on Swap and Mismatch Distance

2023

An edit distance is a metric between words that quantifies how two words differ by counting the number of edit operations needed to transform one word into the other one. A word f is said isometric with respect to an edit distance if, for any pair of f-free words u and v, there exists a transformation of minimal length from u to v via the related edit operations such that all the intermediate words are also f-free. The adjective 'isometric' comes from the fact that, if the Hamming distance is considered (i.e., only mismatches), then isometric words are connected with definitions of isometric subgraphs of hypercubes. We consider the case of edit distance with swap and mismatch. We compare it…

FOS: Computer and information sciencesFormal Languages and Automata Theory (cs.FL)Computer Science - Formal Languages and Automata TheorySwap and mismatch distance Isometric words Overlap with errors
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PRINCIPAL POLYNOMIAL ANALYSIS

2014

© 2014 World Scientific Publishing Company. This paper presents a new framework for manifold learning based on a sequence of principal polynomials that capture the possibly nonlinear nature of the data. The proposed Principal Polynomial Analysis (PPA) generalizes PCA by modeling the directions of maximal variance by means of curves instead of straight lines. Contrarily to previous approaches PPA reduces to performing simple univariate regressions which makes it computationally feasible and robust. Moreover PPA shows a number of interesting analytical properties. First PPA is a volume preserving map which in turn guarantees the existence of the inverse. Second such an inverse can be obtained…

FOS: Computer and information sciencesPolynomialComputer Networks and CommunicationsComputer scienceMachine Learning (stat.ML)02 engineering and technologyReduction (complexity)03 medical and health sciencessymbols.namesake0302 clinical medicineStatistics - Machine LearningArtificial Intelligence0202 electrical engineering electronic engineering information engineeringPrincipal Polynomial AnalysisPrincipal Component AnalysisMahalanobis distanceModels StatisticalCodingDimensionality reductionNonlinear dimensionality reductionGeneral MedicineClassificationDimensionality reductionManifold learningNonlinear DynamicsMetric (mathematics)Jacobian matrix and determinantsymbolsRegression Analysis020201 artificial intelligence & image processingNeural Networks ComputerAlgorithmAlgorithms030217 neurology & neurosurgeryCurse of dimensionalityInternational Journal of Neural Systems
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Classification of spatio-temporal point pattern in the presence of clutter using K-th nearest neighbour distances

2019

In a point process spatio-temporal framework, we consider the problem of features detection in the presence of clutters. We extend the methodology of Byers and Raftery (1998) to the spatio-temporal context by considering the properties of the K-th nearest-neighbour distances. We make use of the spatio-temporal distance based on the Euclidean norm where the temporal term is properly weighted. We show the form of the probability distributions of such K-th nearest-neighbour distance. A mixture distribution, whose parameters are estimated with an EM algorithm, is used to classify points into clutters or features. We assess the performance of the proposed approach with a simulation study, togeth…

FeatureSpatio-temporal point patterns.EarthquakeClutterMixtureEM algorithmNearestneighbour distanceSettore SECS-S/01 - Statistica
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Genetic-based evaluation of management units for sustainable vendace (Coregonus albula) fisheries in a large lake system

2022

The goal of the processing industry, trade and consumers is to get eco-labelled freshwater fish products from sustainable fisheries into the market as soon as possible. The fourth largest natural lake system in Europe, the Saimaa lake system supports a fishery for vendace (Coregonus albula). Certification of the fishery requires an understanding of population structure to help determine the number and spatial extent of management units. In this study, we analysed the genetic diversity of local vendace populations in the Saimaa lake system and aimed to identify the conservation and management units of vendace. Within the Saimaa, the genetic divergence between local populations of vendace was…

Fish stockDesignatable unitmuikkukalakannatGenetic distanceEcolabellingmikrosatelliititkalatalousCoregonidsympäristömerkitpopulaatiogenetiikkakalakantojen hoitoSaimaa lake systemekologinen kestävyys
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Genetic-based evaluation of management units for sustainable vendace (Coregonus albula) fisheries in a large lake system

2022

Abstract The goal of the processing industry, trade and consumers is to get eco-labelled freshwater fish products from sustainable fisheries into the market as soon as possible. The fourth largest natural lake system in Europe, the Saimaa lake system supports a fishery for vendace (Coregonus albula). Certification of the fishery requires an understanding of population structure to help determine the number and spatial extent of management units. In this study, we analysed the genetic diversity of local vendace populations in the Saimaa lake system and aimed to identify the conservation and management units of vendace. Within the Saimaa, the genetic divergence between local populations of ve…

FisheryGenetic divergenceGenetic diversityGeographybiologyGeographical distancePopulation structureFreshwater fishCoregonus albulaLake districtAquatic ScienceLife historybiology.organism_classificationFisheries Research
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