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This labeling at the image level is used to quickly label the corresponding patches.
As introduced in Section 3, our goal is to classify image regions based on the estimated class likelihood ratio of their corresponding patches, as described in (1).
The patches in group (G_{x_{l}}^{j}) can be treated as the corresponding patches in group (G_{y_{l}}^{j}) with high frequency.
For example, Lin et al. modeled the entire scene as an error-free network, where each node corresponds to a patch of the scene and each edge represents the activity correlation between the corresponding patches.
After conducting coregistration between two images acquired before and after the mainshock, we divided the single-look SAR amplitude images into patches and calculated the offset between corresponding patches by using an intensity tracking method.
A third set, containing 485 images of man-made structures in natural landscapes hand-segmented with polygonal shapes to label the corresponding patches (Figure 1) was used to evaluate the methods.
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The corresponding patch is shown in Figure 5 d).
(a - b) precontra - bntensity values and corresprecontrastge patch; (c)-(d) intensity values ander correspondingncement and correspondimageatch.
Therefore, early backouts are likely an indicator that the corresponding patch failed compilation or automated testing.
Usually the patches are overlapping so that each pixel has a corresponding patch, except for the right and bottom regions of the image.
In particular, the center samples of a non-local patches are weighted in proportion to the negative exponential of the corresponding patch distance.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com