Sentence examples for features is then from inspiring English sources

A basic wire-frame aligned with body features is then established based on the parameterized model.

The combination of the two features is then employed in the simulation of motion of drops through constricted tubes.

Each vector of the features is then mapped as a weighted graph and spectral graph wavelet transform is performed.

A sensitive feature subset without irrelevant features or redundant features is then selected based on the proposed IHFST.

Similarity between the two features is then: begin{aligned} s_{text {txt}}(t^1,t^2) = 1 - D v^1,v^2).

The set of extracted features is then projected (through LDA) on a more suited subspace where it is possible to include most of the initial discriminative information in a reduced number of variables.

The locations of ground features are then determined in relation to these triangles by less accurate and therefore cheaper methods.

Geometrical and morphological features are then recognized.

Important features are then illustrated using a full-scale example.

The features are then fed into the classifier.

These features are then fed to trained WNNs.