Sentence examples for between two feature vectors from inspiring English sources

d is the Euclidean distance between two feature vectors with very important texture information.

Operation (b) is the computation of the dissimilarity between two feature vectors.

The MAD between two feature vectors and is calculated as (21).

The dissimilarity between two feature vectors f1 and f2 is denoted as (cleft (mathbf {f}_{1},mathbf {f}_{2}right)).

Additionally, the inner product between two feature vectors is defined as a radial basis function (RBF) kernel to handle nonlinearity.

Commonly used local distances, such as Euclidean or Mahalanobis distances, compute the difference between two feature vectors directly [10], and they are thus of a feature-feature type.

For example, a commonly used dissimilarity measure is the Euclidean norm of the difference between the two feature vectors.

Knowing that X − X′2 is the Euclidean square distance between the two feature vectors and σ is a constant.

In our experiments we have computed the link weights, from the difference, that is, between the two feature vectors and with and without shape context features.

The distance between any two feature vectors v1 and v2 in the DTF space is computed as: d DTF = ∑ i = 1 m ( v 1 i - v 2 i ) 2. (7).

Furthermore, both gene lists give similar separability results despite there being only a small overlap of genes between the two feature vectors.