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The method begins by initializing the parameters needed for the method (line 2).
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Our goal is to align facial parts between the target image and the mean shape by initializing the similarity parameters t1 4 (rotation θ, scaling s, translation (x,y)) (Figure 2).
As the problem is non-convex, we perform the learning process several times, randomly initializing the parameters each time.
The algorithm starts by initializing the cluster centroids.
We begin the simulation by initializing the start source population.
Given, and by initializing, the process of optimization proceeds as follows.
t, and initialize the parameters.
Step 1: Initialize the parameters, including the number of the nodes, and the initialize trust value.
There are various ways to initialize the parameters.
We use a grid search over the parameter space and initialize the parameters to the grid value with highest likelihood.
So the uncertainty caused by random number when initializing the training parameters and the topology of RBF neural network is eliminated.
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