Results 241 to 250 of about 286,362 (268)

Multi-Illuminant Estimation With Conditional Random Fields

IEEE Transactions on Image Processing, 2014
Most existing color constancy algorithms assume uniform illumination. However, in real-world scenes, this is not often the case. Thus, we propose a novel framework for estimating the colors of multiple illuminants and their spatial distribution in the scene. We formulate this problem as an energy minimization task within a conditional random field over
Shida Beigpour, Christian Riess, Joost van de Weijer 0001, Elli Angelopoulou   +3 more
openaire   +2 more sources

Kernel conditional random fields

Twenty-first international conference on Machine learning - ICML '04, 2004
Kernel conditional random fields (KCRFs) are introduced as a framework for discriminative modeling of graph-structured data. A representer theorem for conditional graphical models is given which shows how kernel conditional random fields arise from risk minimization procedures defined using Mercer kernels on labeled graphs.
John D. Lafferty, Xiaojin Zhu 0001, Yan Liu 0002   +2 more
openaire   +1 more source

Neural Gaussian Conditional Random Fields

2014
We propose a Conditional Random Field (CRF) model for structured regression. By constraining the feature functions as quadratic functions of outputs, the model can be conveniently represented in a Gaussian canonical form. We improved the representational power of the resulting Gaussian CRF (GCRF) model by (1) introducing an adaptive feature function ...
Vladan Radosavljevic, Slobodan Vucetic, Zoran Obradovic   +2 more
openaire   +1 more source

Conditioned Stochastic Processes for Conditional Random Fields

Journal of Engineering Mechanics, 1994
Analytical development is presented for the theory of conditional random fields involving conditioning deterministic time functions. After discussion of their basic concept and their engineering significance, the probability distribution of the Fourier coefficients for conditioned stochastic processes is derived.
Kameda, H., Morikawa, H.
openaire   +1 more source

Temperature field in random conditions

International Journal of Heat and Mass Transfer, 1991
Abstract A probabilistic finite-element approach for modelling the temperature field in structures is proposed. The theoretical formulation of the problem is described. It presents probabilistic distributions for temperature taking into account the random thermal properties of material.
openaire   +1 more source

Conditional Random Field

2023
openaire   +1 more source

Uncertainty reduction and sampling efficiency in slope designs using 3D conditional random fields

Computers and Geotechnics, 2016
Philip Vardon
exaly  

Coupled hidden conditional random fields for RGB-D human action recognition

Signal Processing, 2015
An-An Liu, Wei-Zhi Nie, Yuting Su
exaly  

Building Extraction from High Spatial Resolution Remote Sensing Images via Multiscale-Aware and Segmentation-Prior Conditional Random Fields

Remote Sensing, 2020
Qiqi Zhu, Zhen Li, Yanan Zhang
exaly  

Rich features based Conditional Random Fields for biological named entities recognition

Computers in Biology and Medicine, 2007
Chengjie Sun
exaly