Efficient piecewise learning for conditional random fields
Conditional Random Field models have proved effective for several low-level computer vision problems. Inference in these models involves solving a combinatorial optimization problem, with methods such as graph cuts, belief propagation. Although several methods have been proposed to learn the model p...
| Main Authors: | , , |
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| Format: | Conference item |
| Language: | English |
| Published: |
IEEE
2010
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