most citedPerturb-and-MPM: Quantifying Segmentation Uncertainty in Dense Multi-Label CRFs

3 citations · 3 across the 1 of their papers we have counts for

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1 paper

cs.CV2017★ 3 cited

Perturb-and-MPM: Quantifying Segmentation Uncertainty in Dense Multi-Label CRFs

Raphael Meier, Urspeter Knecht, Alain Jungo +2

This paper proposes a novel approach for uncertainty quantification in dense Conditional Random Fields (CRFs). The presented approach, called Perturb-and-MPM, enables efficient, ap…