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The combination of these features is used for expression classification.
The combination of these two types of features is used for facial expression classification.
The description based on these features is used in the recognition step as neural network inputs.
The set of features is used then with SVM classifier to classify data.
The envelope spectrum of the large scale features is used for fault diagnosis.
Then, a generalization of the Shapley index for an arbitrary number of features is used.
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Indeed, their biodegradability is one of the features being used to market them.
Haar features are used.
20 features are used for this evaluation.
These features are used to train the SVM.
The LDA-transformed features were used as the DNN input.
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