参考: https://blog.csdn.net/u012633319/article/details/80921023 二维高斯核, 可以根据下面的公式推到为两个一维高斯核的乘积: 原型: /** @brief Returns Gaussian filter coefficients. The function computes and returns the \f$\texttt{ksize} \times 1\f$ matrix of Gaussian filter coefficien
Radial Basis Functions (RBFs) are set of functions which have same value at a fixed distance from a given central point. Even Gaussian Kernels with a covariance matrix which is diagonal and with constant variance will be radial in nature. In SVMs, RB
import graphviz import mglearn from mpl_toolkits.mplot3d import Axes3D from sklearn.datasets import load_breast_cancer, make_blobs from sklearn.ensemble import RandomForestClassifier from sklearn.model_selection import train_test_split from sklearn.s
首先看下OpenCV 官方文档对于cvSmooth各个参数的解释: Smooths the image in one of several ways. C: void cvSmooth(const CvArr* src, CvArr* dst, int smoothtype=CV_GAUSSIAN, int param1=3, int param2=0, double param3=0, double param4=0) 其对于每个参数的解释如下: param1 – The first para
pcl_common库包含大多数PCL库使用的公共数据结构和方法.核心数据结构包括PointCloud类和许多用于表示点.表面法线.RGB颜色值.特征描述符等的点类型.它还包含许多用于计算距离/范数.均值和协方差.角度转换.几何变换,等等.这个模块是不依赖其他模块的,所以是可以单独编译成功,单独编译出来可利用其中的数据结构自行开发,当然想单独提取出来编译时需要自行修改cmakeLists的,这里就不再赘述. 那么我们就按顺序来解释其中每个函数的作用,有必要的话,我会解释其理论并结合代码实践. P
