Sentence examples for border of the image from inspiring English sources

For example, LaVAN can cause a machine to misclassify a daisy as a jaguar or a subway train as a milk can (as in Fig. 4a), and it can do so even while perturbing only 2% of pixels near the border of the image.

On the other hand, the possibility of occlusion with the border of the image just depends on the proximity of a moving object to the border of the image.

This transformation applies a displacement which is zero at the border of the image and maximum in the center.

It is worth to remember here that, using a 7×7 kernel matrix, a 3-pixel wide border of the image is not filtered, and related pixels are therefore discarded during filtering.

The problem of static occlusion occurs when a mobile object is occluded by the border of the image, or by a static object (e.g. couch, tree, desk, chair, wall and so on).

For instance, there is one visual word that becomes active on blood vessel intersections, as seen in Fig. 4, and another on the macula, although, there are other visual words that are not as interesting, such as one that becomes active on points on the border of the image.

The noisy area at the borders of the image is called the background area.

The image is convoluted with the Laplace-Kernel and the borders of the image are deleted.

We found an increased blurring at the borders of the image, suggesting lens artifacts.

At the borders of the image, where the neighbors do not exist, we set the values of pixels as zeros.

Consequently, the depth noise variance is higher at the borders of the image, as shown in Figure 1. Figure 1 Noise in depth images is highly spatially variable.