Sentence examples for distinctive classification from inspiring English sources

Distinctive classification features were extracted from short-time backscattering bispectrum estimates of the micro-Doppler signature.

Norouzi et al. [48] have proposed distinctive classification techniques with a specific end goal to recognize malware in light of the element and conduct of each malware.

A classification scheme using the Euclidean distance for similarity measures and the between-groups linkage method was performed on the normalized data to produce the most distinctive classification where each member within a group is more similar to its fellow members than to any member outside of the group (Guler and Thyne 2004).

It may also be useful to investigate the hypothesis that the four clusters might correspond to the biological distinction between central and peripheral pain and may overlap with, but provide more distinctive classifications than, those based on location alone.

The GLCM, TFCM, and LBP texture descriptors are employed to extract distinctive features for classification purposes.

The distinctive identification and classification of epiplasmins open the way towards a better-defined functional analysis in Paramecium and Tetrahymena.

lamblia), and some other representative species suspended in deionized water at a maximum flow rate of 12   μL/min, and a maximum of 3000 waterborne parasites can be identified within one minute with a mean accuracy higher than 96% by classification of distinctive scattering patterns using a support-vector-machine (SVM) algorithm.

Shape often carries several types of contour information, which are used as distinctive features for the classification of an object.

For instance, in [1], statistical data extracted from cross-correlation of EEG signals are reported as distinctive features for MI task classification, but the main drawback is the usage of prior information of the classes.

The expanded biological annotation demonstrated that based on DNAm, grouping probes by an alternative high-density and intermediate-density CpG island classification provided a distinctive pattern of DNAm.

end{aligned} (7)  Thus, reflection coefficients acquired from the autocorrelation function of the EEG signal have the potential to form a distinctive feature vector for mental task classification.