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A value is given to this flag by an averaging process for the channels' absolute normalized feature values.
The spar hyper volume spanned by the normalized feature vectors representing different textures must be maximized as well.
Overall, the normalized feature detection methods are shown to be effective in driving the AMR process in an automated and efficient manner.
Normalized feature values between 0 and 1 are extracted from each learning data, which are developed into vector to be used as input vectors for SOM.
The range velocity components are assumed to be 0 m/s. Figure 9 presents the normalized feature curves for T1 and T2.
As described above, the GDA is a nonlinear data dimension reduction method based on kernel function learning technique, which will be used to deal with the normalized feature vectors.
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The currently available estimates are used to normalize features extracted from the current voiced island.
To remove the bias that arises from different ranges of peptide feature values, we normalized each feature as follows: (1) x ′ i = x i − µ i σ i, where x i is the original feature value, and x′ i is the value after normalization; μ i is the mean of the feature values x i across all AMP peptides and σ i is the standard deviation.
Attention estimation accuracies of seven classifiers are shown for each test subject on datasets: a A (normalized features), b A' (normalized with post-filtering), c B (normalized and smoothed features), d B' (with post-filtering), and e C (normalized and smoothed features).
All images were extracted and normalized with Feature Extracter 9.5.
We normalized each feature, scored in different units, to a common scale.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com