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When each image sensor serves as a sensor node, WSN can be employed to classify clouds.
The works presented in [6, 12, 14] applied divide-and-conquer strategy to partition the input space into many disjoint regions, and in each region, a linear or nonlinear SVM can be employed to classify data.
Finally, these sub-BPNNs can be employed to classify instances by fed with a few cycles of post-fault data and output final prediction results based on majority voting.
The proposed algorithm may also be employed to classify other families of enzymes with multi-domain architecture.
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Two Neural Network (NN) classifiers, four Support Vector Machine (SVM) classifiers and K-Nearest Neighbor (KNN) classifier are employed to classify the ECG signals and compared with the proposed classifier.
An HMM classifier was employed to classify each video frame in the arousal-valence axis.
Next, a standard, supervised image classification approach (i.e. Maximum Likelihood Classifier) was employed to classify two major land covers of interest: agricultural land and settlement (urban) areas.
Supervised methods, such as Bayesian classifiers, decision trees and support vector machines, are employed to classify compounds for a particular functional activity class.
For example, when diagnosing cancers based on gene expression profiles, low accuracy is expected if a traditional classifier, for example, linear discriminant analysis (LDA), is employed to classify the samples based on all the genes measured.
To this end, support vector machines (SVMs) [23], nearest-neighbor (NN) classifiers, Gaussian mixture model-based ones [3], and classifiers relying on sparse and low-rank representations [24] have been employed to classify the audio features into genre or mood classes.
In this subsection, PC1DARMF algorithm is employed to classify stochastic fault types.
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