Kernel density estimation 核密度估计
non-parametric kernel density estimation 非参数化的核密度估计
fast Kernel Density Estimation 快速核密度估计
weighted kernel density estimation 加权核密度估计
kernel density function estimation 密度函数核估计
gaussian kernel density estimation 高斯核密度估计
non-parameter kernel density estimation 非参数核密度估计
How to use density kernel estimation for outlier detection?
如何使用密度核估计的孤立点检测？
This method USES kernel density estimation model to construct the approximate density function, and takes hill climbing strategy to extract clustering patterns.
该方法采用核密度估计模型来构造近似密度函数，利用爬山策略来提取聚类模式。
The background samples are chosen by thresholding inter-frame differences, and the Gaussian kernel density estimation is used to estimate the probability density function of background intensity.
通过相隔固定的帧差值阅值化得到背景样本值，并采用高斯核密度估计方法计算背景灰度的概率密度函数。
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