Sentence examples for vectors extraction from inspiring English sources

In this section we introduce the scale invariant feature based method for the landmark detection, which includes three steps: preprocessing, candidate selection and feature vectors extraction.

This paper proposes an improved i-vector extraction algorithm.

NURBS allow modelling through vector extraction from point clouds using mathematical functions.

Figure 2 Single CoLBP feature vector extraction without co-occurrence of features.

The i-vector extraction process was formulated as the MAP estimation problem [13],[13].

The result shows that i-vector extraction consumes much more time than i-supervector.

In Section 4, we propose our CRA algorithm applied in the i-vector extraction phase.

Section 2 describes the construction of total factor matrix and the paradigm of i-vector extraction.

Fig. 5 The overall process of the proposed feature vector extraction method for image splicing detection.

Once the speech segments were identified, the i-vector extraction process was carried out.

The purpose of i-vector extraction is to represent variable-length utterances with fixed-length low-dimensional vectors.