Sentence examples for mean feature vector from inspiring English sources

where μ is the overall mean feature vector of the pixels in R c ⋃ R s.

where μ is the mean feature vector computed on the n points.

where is the number of clusters, is the mean feature vector of th cluster, is the number of the features that belong to cluster, and is the covariance matrix of cluster.

where R1 denotes the region R c, R2 denotes the region R s, x p is the feature vector of pixel p (the vector contains the intensity and color features in the experiments), and μ n is the mean feature vector of the region R n.

In its basic form, CMN consists of subtracting the mean feature vector μ x from each vector x t and normalizing by variance σ x to obtain the normalized vector x ^ t. x ^ t = x t - μ x σ x (7).

NSC represents each class by its centroid (mean feature vector) and classifies new instances by assigning them the class of the closest centroid.

There are two pairs of feature vectors denoted by circles centered at the mean feature vectors.

Mahalanobis distance calculates the distance between two samples based on their mean feature vectors and, and the covariance matrix of the features across all samples in the database.

where βμ is the mean of feature vector of background.

For every scribble, a mean DTF feature vector is obtained and its DTF-distance d DTF (7) to every pixel in the image is computed in the DTF space.

where |R i | is the total number of pixels in patch region R i and (tilde {mathbf {f}}_{i,j}) is the mean-subtracted feature vector.