Results 51 to 60 of about 336,848 (164)

Deep Randomly-Connected Conditional Random Fields For Image Segmentation

IEEE Access, 2017
The use of Markov random fields (MRFs) is a common approach for performing image segmentation, where the problem is modeled using MRFs that incorporate priors on neighborhood nodes to allow for efficient Maximum a Posteriori inference.
Mohammad Javad Shafiee, Alexander Wong, Paul Fieguth   +2 more
doaj   +1 more source

DeepPeptide predicts cleaved peptides in proteins using conditional random fields. [PDF]

Bioinformatics, 2023
Teufel F, Refsgaard JC, Madsen CT, Stahlhut C, Grønborg M, Winther O, Madsen D.   +6 more
europepmc   +1 more source

Random fields

Advances in Mathematics, 1985
Eugene Wong, Bruce Hajek
  +4 more sources

RECURSIVE LINEAR FILTERING OF THE RANDOM DYNAMIC FIELDS UNDER A PRIORI UNCERTAINTY

Весці Нацыянальнай акадэміі навук Беларусі: Серыя фізіка-тэхнічных навук, 2018
The task of filtering random dynamic fields is relevant for a number of applications. To solve it, one can use a statistical approach based on the Kalman filter theory.
V. M. Artemiev, A. O. Naumov, L. L. Kokhan   +2 more
doaj  

On the construction of stationary processes and random fields

Dependence Modeling
We propose a new method to construct a stationary process and random field with a given decreasing covariance function and any one-dimensional marginal distribution. The result is a new class of stationary processes and random fields.
Lee Jeonghwa
doaj   +1 more source

Efficient Inference of Spatially-Varying Gaussian Markov Random Fields With Applications in Gene Regulatory Networks. [PDF]

IEEE/ACM Trans Comput Biol Bioinform, 2023
Ravikumar V, Xu T, Al-Holou WN, Fattahi S, Rao A.   +4 more
europepmc   +1 more source

Learning Traffic Flow Dynamics Using Random Fields

IEEE Access, 2019
This paper presents a mesoscopic traffic flow model that explicitly describes the spatio-temporal evolution of the probability distributions of vehicle trajectories.
Saif Eddin G. Jabari, Deepthi Mary Dilip, Dianchao Lin, Bilal Thonnam Thodi   +3 more
doaj   +1 more source

Blind recovery of sources for multivariate space-time random fields. [PDF]

Stoch Environ Res Risk Assess, 2023
Muehlmann C, De Iaco S, Nordhausen K.
europepmc   +1 more source

An Order Reduction Design Framework for Higher-Order Binary Markov Random Fields. [PDF]

Entropy (Basel), 2023
Chen Z, Yang H, Liu Y.
europepmc   +1 more source

Revisiting Gaussian Markov random fields and Bayesian disease mapping. [PDF]

Stat Methods Med Res, 2023
MacNab YC.
europepmc   +1 more source