Sentence examples for features classification from inspiring English sources

For multidimensional features, classification becomes more difficult.

(b) negative samples. Figure 14 Linear SVM with HOG features classification examples: nonvehicle (red) and vehicle (green).

Methods for skin lesions analysis usually involves three main steps: lesion segmentation, feature extraction, and features classification.

With the selected features, classification error as well as the number of eliminated features is calculated by SVM to evaluate the fitness value for particle i (see Eq. 5).

Advantages and disadvantages of using keystroke dynamics in intrusion detection; Extracted features; Classification algorithms applied; Performance measures commonly adopted; Benchmarking datasets, which are useful for conducting comparative experiments in the area.

The three main parts of the new system are as follows: (a) a novel machining features classification based on machining processes and number of simultaneously controlled axes of five-axis lathe; a new group code system is proposed.

Because convergent evolution leads to broad similarity in morphological features, classifications and phylogenies based mainly on morphology make identification of such convergence in a single group more difficult.

This paper discusses three different issues in feature classification.

For more complex cases, the target is the development of feature classification and feature extraction schemes.

It is observed that there are three major steps: (i) coarse feature classification, (ii) contour segmentation, and (iii) fine feature classification.

The second algorithm, GFP.MC, constructs feature intervals by greedily improving the feature classification error.