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In the output layer of the network, the softmax classifier is applied to classify samples.
Secondly, the Softmax classifier is applied to classify the precipitation patterns, including rain, snow, and hail, and it is based on the features extracted by deep learning algorithm.
Moreover, the Softmax classifier is applied to classify the precipitation pattern such as rain, snow, and hail based on the features extracted by the convolution neural network algorithm.
Then if RotBoost ensemble classifier is applied to classify such dataset directly, a rotation matrix with thousands of dimensions is required for each tree, which greatly increases the computational complexity.
Finally, the quadratic discriminant classifier described in Section 2.5 is applied to classify protein sequences.
Finally, ANN-PSO method is applied to classify the inputs as potato plants or weeds.
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Cluster analysis was applied to classify the forest types.
Specifically, singularity theory and bifurcation theory are applied to classify the bifurcation behavior of the system.
In 87 images, intensity thresholds were applied to classify each pixel into one of four categories.
The method may be applied to classify species within other bacterial genera.
The zoom rule can be applied to classify photos according to the distance from the camera to the subject.
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