Sentence examples for class recognition from inspiring English sources

SVM is basically designed to solve two class recognition problems.

Different feature selection methods have resulted in changing average accuracy of the class recognition.

The non-zero class recognition errors are due to the non-unique characteristics of the images in the data sets.

As a result, we have selected only six features treated as the most important for the class recognition.

The task is to select the features which are important to the class recognition but at the same time not redundant to any of the other relevant features.

The system uses a statistical part-of-speech tagger for word class recognition and subsequently uses semantic and pragmatic information to construct possible relations.

He became an international superstar, the only hair stylist – or crimper, as he might put it – who ever achieved international, world-class recognition.

(a) Inter-class recognition (Case I).

(b) Inter-class recognition (Case II).

Figure 10 False recognition probability versus number of symbols (inter-class recognition, full-class recognition, intra-class QAM recognition, and Intra-class FSK recognition).

Using Haar wavelet, our previous results show that the for full-class recognition is 4 dB.