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We repeated our experiments with other graph clustering algorithms such as O RCA[ 25], which is strong on very large graphs, minimum-cut tree clustering [ 26], which is able to guarantee certain bottleneck properties of clusters, and iterative conductance clustering [ 27], which features a parameterized clustering coarseness.
Most graph-based segmentation methods attempt to search a certain structures in the associated edge weighted graph constructed on the image pixels, such as minimum spanning tree [20, 21], or minimum cut [22, 23].
Moreover, Minimum Cut Sets (MCS) and importance calculation are applied to analyze the fault tree quantitatively.
Since Cut 1 satisfies the constraint of coherence/separation, it is a probable minimum cut.
Coppices of cut tree stumps were positively correlated with tree regeneration (r=0.522, P<0.0001).
This was also the case in models for live trees, cut trees, and natural mortality using plots for which cut tree data were available (221 of 284).
The minimum cut of the graph is the cut such that the sum of the weights of the edges belonging to its cut-set is minimum.
Cut tree shape from cardboard.
Buy a freshly cut tree.
They cut trees.
Now he visits mostly to cut trees.
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