Results 31 to 40 of about 169,073 (281)
The Annals of Applied Probability, 1995 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kunsch, Hans +2 more
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Simulating Lagrangian Subgrid‐Scale Dispersion on Neutral Surfaces in the Ocean
Journal of Advances in Modeling Earth Systems, 2022 To capture the effects of mesoscale turbulent eddies, coarse‐resolution Eulerian ocean models resort to tracer diffusion parameterizations. Likewise, the effect of eddy dispersion needs to be parameterized when computing Lagrangian pathways using coarse ...
Daan Reijnders +2 more
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3D CLASSIFICATION OF CROSSROADS FROM MULTIPLE AERIAL IMAGES USING MARKOV RANDOM FIELDS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2012 The precise classification and reconstruction of crossroads from multiple aerial images is a challenging problem in remote sensing. We apply the Markov Random Fields (MRF) approach to this problem, a probabilistic model that can be used to consider ...
S. Kosov +4 more
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Outage Estimation in Electric Power Distribution Systems Using a Neural Network Ensemble
Energies, 2021 Outages in an overhead power distribution system are caused by multiple environmental factors, such as weather, trees, and animal activity. Since they form a major portion of the outages, the ability to accurately estimate these outages is a significant ...
Sanjoy Das +2 more
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Bayesian 2D Deconvolution: A Model for Diffuse Ultrasound Scattering [PDF]
Modeling, Identification and Control, 2001 Observed medical ultrasound images are degraded representations of the true acoustic tissue reflectance. The degradation is due to blur and speckle, and significantly reduces the diagnostic value of the images. In order to remove both blur and speckle we
Oddvar Husby +4 more
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Computing the Cramer-Rao bound of Markov random field parameters: Application to the Ising and the Potts models [PDF]
, 2013 This report considers the problem of computing the Cramer-Rao bound for the parameters of a Markov random field. Computation of the exact bound is not feasible for most fields of interest because their likelihoods are intractable and have intractable ...
Batatia, Hadj +3 more
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Collaborative filtering via sparse Markov random fields
, 2016 Recommender systems play a central role in providing individualized access to information and services. This paper focuses on collaborative filtering, an approach that exploits the shared structure among mind-liked users and similar items. In particular,
Phung, Dinh +2 more
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Adaptive Gaussian Markov Random Fields with Applications in Human Brain Mapping [PDF]
, 2005 Functional magnetic resonance imaging (fMRI) has become the standard technology in human brain mapping. Analyses of the massive spatio-temporal fMRI data sets often focus on parametric or nonparametric modeling of the temporal component, while spatial ...
Brezger, Andreas +2 more
core +2 more sources
High-Order Markov Random Fields and Their Applications in Cross-Language Speech Recognition
Cybernetics and Information Technologies, 2015 In this paper we study the cross-language speech emotion recognition using high-order Markov random fields, especially the application in Vietnamese speech emotion recognition.
Zhipeng Jiang, Chengwei Huang
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Comparison of linear discriminant functions in image classification
Lietuvos Matematikos Rinkinys, 2010 In statistical image classification it is usually assumed that feature observations given labels are independently distributed. We have retracted this assumption by proposing stationary Gaussian random field (GRF) model for features observations ...
Lijana Stabingienė +2 more
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