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The behavior regularity level for the remaining subjects can be assessed using the same two types of regularity, which helps explain why with some individuals the results were significantly better while, with others, our algorithm was struggling to produce accurate predictions.
A distance regularity level set method is proposed in [ 13].
Finally the modified distance regularity level set method utilizes boundaries feature and probability density to conform final object.
Based on optimal initial zero level set, extract the object using a priori based distance regularity level set method.
A priori based distance regularity level set method is applied to extract the object organ in CT images.
In order to solve these problems, we employ a priori statistical feature to modify distance regularity level set as well as confirming an optimal initial level set.
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The notion of latent periodicity in nucleotide DNA sequences has arisen from the discovery of various regularity levels in the structural organization of a DNA molecule.
To preserve the regularity of the level set function ϕ, a level set regularization term P = ∫Ω x (|∇ ϕ(x)|−1)/2 dx is introduced, which is necessary for accurate computation and the stable evolution.
Therefore, a frequent re-initialization process, formulated as ∂Φ/∂t = sign Φ0) (1 - ||∇Φ||), could be included to restore the regularity of the level set function, establishing a stable level set evolution.
In order to study the sensitivity analysis of the negative value function in the lower-level problem (3.1), we first recall the lower-level and upper-level regularity conditions [40], which are defined, respectively, as ∑ i = 1 p β i ∇ z g i ( x ∗, z ∗ ) = 0, β i ≥ 0, β i g i ( x ∗, z ∗ ) = 0, i = 1, …, p } ⇒ β i = 0, i = 1, …, p, (4.4).
The regularizing term P ϕ intrinsically maintains the regularity of the level set function without the need for extra re-initialization procedures.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com