Results 241 to 250 of about 168,985 (282)

Markov Random Fields

2015
This chapter presents an introduction to Markov random fields (MRFs), also known as Markov networks, which are undirected graphical models. We describe how a Markov random field is represented, including its structure and parameters, with emphasis on regular MRFs.
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Causal Markov Random Fields

2004
Traditionally two groups have developed extensions of 1-D Markov processes to 2-D image data. People in the first group adopt most of their ideas and tools from statistical mechanics and express the Markov nature of a random field in a noncausal way. The MRFs described in Chapter 2 are such models.
Chee Sun Won, Robert M. Gray
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Morphological Markov random fields

Statistics & Probability Letters, 1994
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Molecular imaging in oncology: Current impact and future directions

Ca-A Cancer Journal for Clinicians, 2022
Steven P Rowe, Martin G Pomper
exaly  

Markov Random Fields.

Journal of the American Statistical Association, 1984
Robert J. Adler, Yu A. Rozanov
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Machine Learning Force Fields

Chemical Reviews, 2021
Oliver T Unke, Stefan Chmiela, Huziel E Sauceda   +2 more
exaly  

Management of glioblastoma: State of the art and future directions

Ca-A Cancer Journal for Clinicians, 2020
Aaron Tan, David M Ashley, Giselle Lopez
exaly  

Transforming heat transfer with thermal metamaterials and devices

Nature Reviews Materials, 2021
Ying Li, Wei Li, Tiancheng Han
exaly  

Markov random field

2001
Saul I. Gass, Carl M. Harris
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Markov Random Fields

1982
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