Name
Abstract | ||
|---|---|---|
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. These local MRF models often result in smoothed segmentation boundaries, since they penalize the assignment of different labels to neighboring pixels and are limite... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/ACCESS.2016.2603976 | IEEE Access |
Keywords | Field | DocType |
Image segmentation,Computational modeling,Biological system modeling,Stochastic processes,Smoothing methods,Streaming media,Markov random fields | Stochastic optimization,Random graph,Computer science,Image segmentation,Artificial intelligence,Random function,Distributed computing,Conditional random field,Stochastic simulation,Random field,Pattern recognition,Algorithm,Variable-order Markov model | Journal |
Volume | ISSN | Citations |
5 | 2169-3536 | 2 |
PageRank | References | Authors |
0.36 | 24 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| M. J. Shafiee | 1 | 100 | 22.85 |
| Alexander Wong | 2 | 351 | 69.61 |
| Paul W. Fieguth | 3 | 612 | 54.17 |