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Partially Observed Markov Random Fields Are Variable Neighborhood Random Fields
(SPRINGERNEW YORK, 2012)
The present paper has two goals. First to present a natural example of a new class of random fields which are the variable neighborhood random fields. The example we consider is a partially observed nearest neighbor binary ...
The use of discrete Markov random fields in reservoir characterization
(Elsevier Science BvAmsterdamHolanda, 2001)
Reference fields analysis of a Markov random field model to improve image segmentation
(Journal of Applied Research and Technology, 2010)
Reference fields analysis of a Markov random field model to improve image segmentation
(Journal of Applied Research and Technology, 2010)
Using a Markov Random Field for Image Re-ranking Based on Visual and Textual Features
(Revista Computación y Sistemas; Vol. 14 No. 4, 2011-06-06)
Abstract. We propose a novel method to re-order the list of images returned by an image retrieval system (IRS). The method combines the original order obtained by the IRS, the similarity between images obtained with visual ...
OPF-MRF: Optimum-path forest and Markov random fields for contextual-based image classification
(2013-09-26)
Some machine learning methods do not exploit contextual information in the process of discovering, describing and recognizing patterns. However, spatial/temporal neighboring samples are likely to have same behavior. Here, ...
Extraction of Building Roof Contours From LiDAR Data Using a Markov-Random-Field-Based Approach
(Institute of Electrical and Electronics Engineers (IEEE), 2012-03-01)
This paper proposes a method for the automatic extraction of building roof contours from a digital surface model (DSM) by regularizing light detection and ranging (LiDAR) data. The method uses two steps. First, to detect ...
OPF-MRF: Optimum-path forest and Markov random fields for contextual-based image classification
(2013-09-26)
Some machine learning methods do not exploit contextual information in the process of discovering, describing and recognizing patterns. However, spatial/temporal neighboring samples are likely to have same behavior. Here, ...