This paper describes a new Euclidean Similarity factor (ESF) based active contour model with deep learning for segmenting the tumor region into complete, core and enhanced tumor portions. Initially, the ESF considers the spatial distances and intensity differences of the region automatically to detect...
A simple and straightforward way to quantify shape similarity is to calculate the Pearson correlation between two profiles (r12). Because the correlation is unaffected by elevation and scatter, it is a “pure” index of shape similarity, and performs well even in comparison with more complex indi...
Networks of disparate phenomena—be it the global ecology, human social institutions, within the human brain, or in micro-scale protein interactions—exhibit broadly consistent architectural features. To explain this, we propose a new theory where link p
Familiar examples of 2-manifolds are a sphere and a torus; evidently each has some residual local similarity to pieces of the Euclidean plane E2 from which they are synthesized, but globally they are very different. One geometrical difference is already apparent: in the Euclidean plane the angle...
First we introduce (a) the (Euclidean) Squared Exponential (SE) kernel, working on weight vectors—so, computing the similarity between two distributions depending on the Euclidean distance between their weight vectors—and (b) the Wassertein Squared Exponential (WSE) kernel—computing the similarity...
In the Full-reference quality metric, there are three algorithms used to check the quality of the image, they are image mean square error (MSE), image peak signal-to-noise ratio (PSNR), and image Structural Similarity Index (SSIM). MSE and PSNR are simple to calculate it is given in ...
1.Thegeneralized Euclidean distanceincluding such parameters as position,velocity and threat index is defined.定义了包含位置、速度和威胁指数等参数的广义欧式距离,运用最近邻法和以目标角度为启发信息地全局A*搜索算法对目标聚类分群。 2)general Euclid distance广义欧氏距离 ...
1. The generalized Euclidean distance including such parameters as position,velocity and threat index is defined. 定义了包含位置、速度和威胁指数等参数的广义欧式距离,运用最近邻法和以目标角度为启发信息地全局A*搜索算法对目标聚类分群。2) general Euclid distance 广义欧氏距离 1. On the basis of ...
More generally, for self-similar sets where each piece is scaled by a possibly different factor ri, the similarity dimension is the unique positive root d of the Moran equation ∑i=1Nrid=1. The relation 0 ≤ dsim ≤ E. If the fractal is a subset of E-dimensional Euclidean space, E ...
Hence, the parallelization techniques to be discussed can also be applied to other incrementally accumulated similarity measures such as the Pearson correlation coefficient of two z-normalized (vanishing mean and unit variance) random variables x(i) and y(j) (6.6)ρ(x(i),y(j))=∑k=0d−1...