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By these processes, it can obtain nonlinear classification features efficiently.
We also use words and POSs as classification features.
Than obtained Wavelet coefficients by Discrete Wavelet Transform (DWT) and determined classification features from Wavelet coefficients.
One of the aspects of signal classification is the selection of proper classification features.
Distinctive classification features were extracted from short-time backscattering bispectrum estimates of the micro-Doppler signature.
Classification features based on the bispectrum estimate have been proposed earlier [11, 12].
The discriminant classification features are obtained by analyzing the atoms parameters.
In this paper we focus on the continuous wavelet transform (CWT) to extract the classification features.
It includes two processes: raising dimensions to get nonlinear information and reducing dimensions to get classification features.
Systole and diastole shown as t12 and t21, respectively, in Fig. 2 serve as important beat classification features.
After a short limited preview, Google today announced the public beta of its Cloud Vision API — a service that allows developers to easily build image recognition and classification features into their applications.
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