Results 41 to 50 of about 169,073 (281)
Markov Random Field Surface Reconstruction [PDF]
IEEE Transactions on Visualization and Computer Graphics, 2010 A method for implicit surface reconstruction is proposed. The novelty in this paper is the adaptation of Markov Random Field regularization of a distance field. The Markov Random Field formulation allows us to integrate both knowledge about the type of surface we wish to reconstruct (the prior) and knowledge about data (the observation model) in an ...
Paulsen, Rasmus Reinhold +2 more
openaire +3 more sources
Gaussian mixture model and Markov random fields for hyperspectral image classification
European Journal of Remote Sensing, 2018 This paper presents a novel method for reliable and efficient spatial-spectral classification of hyperspectral data. This algorithm is based on the Bayesian labelling by combining the results of the Gaussian mixture model (GMM) with spatial-contextual ...
Hamid Ghanbari +3 more
doaj +1 more source
Statistical paleoclimate reconstructions via Markov random fields
, 2015 Understanding centennial scale climate variability requires data sets that are accurate, long, continuous and of broad spatial coverage. Since instrumental measurements are generally only available after 1850, temperature fields must be reconstructed ...
Emile-Geay, Julien +2 more
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Consistent estimation of the basic neighborhood of Markov random fields [PDF]
, 2006 For Markov random fields on $\mathbb{Z}^d$ with finite state space, we address the statistical estimation of the basic neighborhood, the smallest region that determines the conditional distribution at a site on the condition that the values at all other ...
Csiszár, Imre, Talata, Zsolt
core +4 more sources
Submodular relaxation for inference in Markov random fields
, 2015 In this paper we address the problem of finding the most probable state of a discrete Markov random field (MRF), also known as the MRF energy minimization problem. The task is known to be NP-hard in general and its practical importance motivates numerous
Osokin, Anton, Vetrov, Dmitry
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Identifying protein complexes directly from high-throughput TAP data with Markov random fields
BMC Bioinformatics, 2007 Background Predicting protein complexes from experimental data remains a challenge due to limited resolution and stochastic errors of high-throughput methods. Current algorithms to reconstruct the complexes typically rely on a two-step process.
Krause Roland +3 more
doaj +1 more source
Markov random fields and Markov chains on trees [PDF]
, 1981 We consider probability measures on a space S(^A) (where S and A are countable and the σ-field is the natural one) which are Markov random fields with respect to a given neighbour relation ~ on A.
Zachary, Stan
core
Advanced Optical Materials, EarlyView.A dual‐domain PSLC architecture enables direct comparison of alignment‐dependent laser damage within a single device. Crack‐like and seal‐like morphologies emerge under different damage conditions, and their evolution is interpreted through quantitative image analysis and heat‐driven simulations.
Dengcheng Chen +4 more
wiley +1 more source
Adaptive Markov Random Fields for Example-Based Super-resolution of Faces
EURASIP Journal on Advances in Signal Processing, 2006 Image enhancement of low-resolution images can be done through methods such as interpolation, super-resolution using multiple video frames, and example-based super-resolution.
Stephenson Todd A, Chen Tsuhan
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COMBINE MARKOV RANDOM FIELDS AND MARKED POINT PROCESSES TO EXTRACT BUILDING FROM REMOTELY SENSED IMAGES [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2012 Automatic building extraction from remotely sensed images is a research topic much more significant than ever. One of the key issues is object and image representation.
D. Chai, W. Förstner, M. Ying Yang
doaj +1 more source