Random field-based regional liquefaction hazard mapping — data inference and model verification using a synthetic digital soil field
Sign Up to like & getrecommendations! Published in 2017 at "Bulletin of Engineering Geology and the Environment"
DOI: 10.1007/s10064-017-1071-y
Abstract: Geostatistical tools and random field models have been increasingly used in recent liquefaction mapping studies. However, a systematic verification and assessment of random field models has yet to be taken, and implications of various random… read more here.
Keywords: random field; field; liquefaction; model ... See more keywords
Exponential Decay of Correlations in the 2D Random Field Ising Model
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Statistical Physics"
DOI: 10.1007/s10955-019-02401-5
Abstract: An extension of the Ising spin configurations to continuous functions is used for an exact representation of the random field Ising model’s order parameter in terms of disagreement percolation. This facilitates an extension of the… read more here.
Keywords: exponential decay; random field; field ising; ising model ... See more keywords
An information-theoretic wavelet-based texture descriptor using Gaussian Markov random field models
Sign Up to like & getrecommendations! Published in 2019 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-019-07916-3
Abstract: Texture characterization and identification is a key issue for a variety of computer vision and image processing applications. Current techniques developed for dealing with the purpose thereof still present performance issues when applied in the… read more here.
Keywords: information; markov random; random field; texture descriptor ... See more keywords
Cauchy Markov random field priors for Bayesian inversion
Sign Up to like & getrecommendations! Published in 2022 at "Statistics and Computing"
DOI: 10.1007/s11222-022-10089-z
Abstract: The use of Cauchy Markov random field priors in statistical inverse problems can potentially lead to posterior distributions which are non-Gaussian, high-dimensional, multimodal and heavy-tailed. In order to use such priors successfully, sophisticated optimization and… read more here.
Keywords: random field; field priors; markov random; cauchy ... See more keywords
A Gaussian random field model for de-speckling of multi-polarized Synthetic Aperture Radar data
Sign Up to like & getrecommendations! Published in 2019 at "Advances in Space Research"
DOI: 10.1016/j.asr.2019.03.013
Abstract: Abstract Synthetic Aperture Radar (SAR) data have gained interest for a variety of remote sensing applications, given the capability of SAR sensors to operate independent of solar radiation and day/night conditions. However, the radiometric quality… read more here.
Keywords: synthetic aperture; method; random field; aperture radar ... See more keywords
A Markov random field integrating spectral dissimilarity and class co-occurrence dependency for remote sensing image classification optimization
Sign Up to like & getrecommendations! Published in 2017 at "Isprs Journal of Photogrammetry and Remote Sensing"
DOI: 10.1016/j.isprsjprs.2017.03.020
Abstract: Abstract This paper develops a novel Markov Random Field (MRF) model for edge-preserving spatial regularization of classification maps. MRF methods based on the uniform smoothness lead to oversmoothed solutions. In contrast, MRF methods which take… read more here.
Keywords: classification; markov random; random field; remote sensing ... See more keywords
Learning a constrained conditional random field for enhanced segmentation of fallen trees in ALS point clouds.
Sign Up to like & getrecommendations! Published in 2017 at "Isprs Journal of Photogrammetry and Remote Sensing"
DOI: 10.1016/j.isprsjprs.2017.04.001
Abstract: Abstract In this study, we present a method for improving the quality of automatic single fallen tree stem segmentation in ALS data by applying a specialized constrained conditional random field (CRF). The entire processing pipeline… read more here.
Keywords: conditional random; random field; field; segmentation ... See more keywords
De-identification of clinical notes via recurrent neural network and conditional random field.
Sign Up to like & getrecommendations! Published in 2017 at "Journal of biomedical informatics"
DOI: 10.1016/j.jbi.2017.05.023
Abstract: De-identification, identifying information from data, such as protected health information (PHI) present in clinical data, is a critical step to enable data to be shared or published. The 2016 Centers of Excellence in Genomic Science… read more here.
Keywords: conditional random; challenge; random field; recurrent neural ... See more keywords
Dynamics analysis of slender vehicle influenced by random factors
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Fluids and Structures"
DOI: 10.1016/j.jfluidstructs.2020.103086
Abstract: Abstract In this paper, the aeroelastic problems of slender vehicles under the influence of random factors and thrust are studied. An aeroelastic dynamic model of a free-free Euler–Bernoulli beam considering thrust and aerodynamic forces is… read more here.
Keywords: random field; random factors; correlation; analysis ... See more keywords
Sketch simplification based on conditional random field and least squares generative adversarial networks
Sign Up to like & getrecommendations! Published in 2018 at "Neurocomputing"
DOI: 10.1016/j.neucom.2018.07.065
Abstract: Abstract Sketch simplification is a critical part of cartoon drawing work. Some existing approaches are already capable of simplifying simple sketches, but in some cases, they are still insufficient because of method diversity of sketch… read more here.
Keywords: sketch simplification; simplification; random field; conditional random ... See more keywords
Imprecise random field analysis with parametrized kernel functions
Sign Up to like & getrecommendations! Published in 2019 at "Mechanical Systems and Signal Processing"
DOI: 10.1016/j.ymssp.2019.106334
Abstract: Abstract The application of isotropic random fields in engineering analysis requires the definition of their first two central moments, as well as their covariance function. In general, insufficient data are available to make a fully… read more here.
Keywords: random field; field; field analysis; imprecise random ... See more keywords