高斯混合模型在图像处理中的扩展 Gaussian Mixture Model in Image Processing Explained,程序员大本营,技术文章内容聚合第一站。
The Gaussian mixture model (GMM) is well-known as an unsupervised learning algorithm for clustering. Here, “Gaussian” means the Gaussian distribution, described by mean and variance;mixturemeans the mixture of more than one Gaussian distribution. The idea is simple. Suppose we know a collection ...
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Blömer, J. and Bujna, K., 2013. Simple methods for initializing the em algorithm for gaussian mixture models. CoRR. Kwedlo, W., 2013. A new method for random initialization of the EM algorithm for multivariate Gaussian mixture learning. In Proceedings of the 8th International Conference on...
Fig. 5. Variance in cohorts explained in the GM-3DMM. In view of 2D face image fitting and recognition, where one of the key challenges is to select the correct mixture component, we compare the GM-3DMM to the standard global 3DMM and to the individual cohort models (where covariance ...
The unsupervised learning algorithm based on Gaussian mixture models called Gaussian-based dynamic probabilistic clustering (GDPC) is one of these tools. However, this algorithm may have major limitations if a large amount of concept drifts associated with transients occurs within the data stream. GDPC...
single pass learning by defining the class PDF for each of the brainwave pattern in the frequency domain using Gaussian mixture model (GMM)59,60. GMM is represented as the weighted sum of a finite number of scaled (different variance) and shifted (different mean) normal distributions as describ...
Gaussian mixture modelSupport vector data descriptionStatistical pattern analysisNeyman Pearson lemmaTraditional multivariate statistical process monitoring techniques usually assume measurements follow a multivariate Gaussian distribution so thatT2can be used for monitoring. The assumption usually does not hold in...
The selected models and explained variances of each component for all 1538 proteins are reported in Supplementary Data 3. We detected 38 proteins that are associated with the group covariate. In the original analyses by Liu et al.15 [Table 1 and Supplementary Table S3], 18 of these proteins ...
Indeed, recently, using tools from random matrix theory, it was shown in [DM05] that in many cases the mutual information of MIMO models has an asymptotically Gaussian behavior. Random matrices were first proposed by Wigner in quantum mechanics to explain the measured energy levels of nuclei in...