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The shape of targets or a context of distracting objects did not affect accuracy or speed.
When we use direct imaging methods for solving inverse scattering problems, we observe artificial lines which make it hard to determine the shape of targets.
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Generally, the shape of target distribution is characterized by its mode and width.
The simulation results show that the proposed device not only can visually shift the image of target in two dimensions, but also can visually transform the shape of target.
The same arguments apply for localization and, especially, for shapes of targets.
First, without the help of stereology, users need to explicitly provide the 3D shapes of target particles for synthesis.
Unlike bounding boxes used in ImageNet, our single model can draw the shapes of target objects, and in the meanwhile, classify the objects and calculate their sizes.
Finally, the shape of the target object can be quantitatively obtained as follows: Δ L x, y, d = λ 2 π Δ ϕ x, y, d Δ n x, y, d (18).
It is also possible to analyze the size and the shape of each target object by observing its corresponding connected component.
But occasionally, one of the muons will happen to hit an atomic nucleus, and when it does, it will change direction in a way that gives a clue about the shape of the target and the target's density.
Subjects maintained either the location or the shape of the targets in WM and responded to each probe by indicating whether it was a target.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com