Sentence examples for foreground classes from inspiring English sources

EGMM, which assigns multiple foreground classes, has the inverse problem: it gets drowned in false positives, only performing reasonably well in one sequence (MW03, Figure 6).

Instead, as in[11], [12], for each population we compared the DAF distribution of the foreground classes of sites directly with the three control classes of sites (all assumed to be evolving neutrally).

One verifies a test pixel for the shadow class (10) and another verifies for the foreground class (11): (10).

The preferential treatment of the foreground class is intended at this stage of processing to keep the detection rate high.

This cost estimate is refined along the edges to compensate for any over or under estimation of the foreground class using a primal-dual approach.

We reject all segments that are predicted to belong to the background class and keep only segments predicted to be members of the foreground class.

Due to the asymmetry between the two sets of color, we assign the foreground class higher misclassification costs than the background class.

Foreground class variance σ 1 2 = ∑ i = k + 1 L ( i - μ 1 ) 2 p i ω 1 (7)where the total mean is μ T = ∑ i = 1 L i p i (8).

However, the log likelihood is lower and the ω3 estimate for the foreground divergent class is larger when only considering the Eutherian UCP1 clade (clade E).

Then the blocks are manually labeled into two classes: foreground blocks and background blocks.

Binarization is a classification process in which intra-image pixels are assigned to either of the two following classes: foreground text and background.