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Conditional Random Fields for Image Labeling
2016
Mathematical Problems in Engineering
With the rapid development and application of CRFs (Conditional Random Fields) in computer vision, many researchers have made some outstanding progress in this domain because CRFs solve the classical version of the label bias problem with respect to MEMMs (maximum entropy Markov models) and HMMs (hidden Markov models). This paper reviews the research development and status of object recognition with CRFs and especially introduces two main discrete optimization methods for image labeling with
doi:10.1155/2016/3846125
fatcat:oq4pelbyz5c5ris7o7xl22rvva