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与 目标函数 相关的网络例句 [注:此内容来源于网络,仅供参考]

The Absolute Wavelet Affine Invariant Function is constructed based on WAIF,and is used as the eigenvector of the object to be recognized,and is combined with Convex Hull for object recognition.

基于小波仿射不变函数构造了绝对小波仿射不变函数,作为待识别目标的特征向量,与凸壳相结合进行目标识别。

Our approach consists of the following steps: providing a sketch based mapping between the sources and the target; deforming the target based on the deformations of the corresponding sources by means of differential mean value coordinates; smoothing the deformed target with constrained minimization method to form a key frame of the target animation; and interpolating between key frames created from to produce a complete 3D animation of the target.

该框架由以下几个步骤组成:使用草图在源网格和目标网格间建立映射;使用非闭合网格均值坐标,根据源动画的运动风格来变形目标网格;对变形后的目标网格求解最小化约束函数以获取光滑的目标网格,从而生成目标动画的关键帧;对由产生的结果进行插值,产生完整的目标对象的三维动画。

The second research has also got that a function of slopes to C values is monotone decreasing function when target circles are bigger than distractors circles.

研究二针对目标圆大于干扰子圆大的条件,得到的目标搜索斜率对C值的函数也是单调递减函数,并确定了平行搜索与系列搜索的临界点〓(0.497)。

It is composed of a deformable parametric curve and corresponding energy function.

主动轮廓模型是一种基于高层信息的目标轮廓特征提取算法,它由一条可变形的参数曲线及其相应的能量函数组成,以最小化能量函数为目标,控制参数曲线变形,具有最小能量的闭合曲线就是目标轮廓。

An indicator sampling method is proposed for visualizing a three dimensional penetrable obstacle from a knowledge of far field data for time harmonic acoustic scattered waves.

提出了用时谐声散射场的远场信息来可视化三维可穿透目标的一种指示器样本方法,它是通过析取一个指示器函数在包含可穿透目标的某个样本区域中的支集来实现这种可视化的,其中,这个指示器函数在可穿透目标的内部和外部有显著不同的取值。

Without utility function, group preference relation on alternative set was constructed in this paper by means of efficient numbers of a lternatives, which are described by Pareto efficient solutions of a group of mul tiobjective decision making problems respectively considered by decision makers.

一些学 者曾借助群体效用函数引进群体多目标决策问题有关效用解的概念,并且给出若干求解的方法。本文撇开效用函数的介入,直接依据由各多目标决策问题的Pareto有效解表示的供选方案的有效数,引进了决策群体在供选方案集上的偏爱关系。

Aiming at complicated computing and difficulty of being realized when extending single sensor PHD filtering to the multi-sensor case by means of probability generating function, a multi-sensor multi-target sequential particle-PHD tracking algorithm is proposed based on the thought of sequential filtering for a centralized fusion system. The algorithm chooses the importance density function with regard to every sensor, and updates sample particle of every sensor layer by layer.

当采用概率母函数将单传感器PHD滤波推广到多传感器情形时,针对计算繁琐,难于实现的问题,本文基于集中式融合系统的有序滤波思想,提出多传感器、多目标有序粒子PHD跟踪算法,该算法通过选取与各传感器相关的重要性密度函数,层层更新各传感器的采样粒子,达到多传感器多目标有序PHD跟踪。

In the algorithm,the theory of particle system changing from non-equilibrium to equilibrium is used to define the Rank function and Niche function for solving multi-objective problems,all the individuals in the population have chance to participate the evolving operation to solve the Pareto optimal solutions of the multi-objective problems fast and evenly.

由于该算法使用了粒子系统从非平衡达到平衡的理论来定义求解多目标问题的Rank函数和Niche适应值函数,使得种群中的所有个体都有机会参与演化操作,以达到快速、均匀地求出多目标优化问题的Pareto最优解。

The traditional mean shift algorithm requires a symmetric kernel, such as a circle or a rectangle, and assumes that the target's scale is symmetric during the course of tracking. The pixels are used on the edge as the samples, about 5% to 10% of the total pixels in the kernel.

与采用对称核函数的均值迁移目标跟踪算法相比,采用目标边缘点作为核函数中的样本点,参与计算的样本点为核窗口中样本的5%~10%,使图像处理速度达到了50帧/s以上,满足了实时跟踪的要求。

The traditional mean shift algorithm requires a symmetric kernel, such as a circle or a rectangle, and assumes that the target's scale is symmetric during the course of tracking.

与采用对称核函数的均值迁移目标跟踪算法相比,采用目标边缘点作为核函数中的样本点,参与计算的样本点为核窗口中样本的5%~10%,使图像处理速度达到了50 帧/s 以上,满足了实时跟踪的要求。

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然而,正如其名字所指出的那样,CD盘不能写,也不能用任何方式改变其内容。

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