Exact(7)
That is, if we represent the total number of pixels in one SCD as npSum, then in individually normalizing method, the normalized SCD is defined as: s norm 2 = n p 1 npSum, n p 2 npSum, …, n p i npSum, …, n p 60 npSum.
This normalizing method accounts for absolute change over time because normalized indicators within an identical range have much more similar variability than the original ones.
Individually normalizing method eliminates these differences.
"Std-norm" and "Ind-norm" refer to standard deviation normalizing method and individually normalizing method (refer to Section Weak pose estimation using GPR).
In individually normalizing method, we divide the pixel number in a bin by the total pixel number of the SCD.
Table 5 Action recognition accuracy of our individually normalizing method for IXMAS dataset using the models learnt from HumanEva dataset compared with the method prosed in [[43]] Accuracy Punch Wave Throw a ball Walk All actions Ind-normal 75.0 75.0 75.075.075.0 [43] 86.8 75.0 82.4 75.0 82.2.
Similar(53)
Popular normalizing methods include lowess and loess smoothers to remove systematic sources of noise [ 3, 4].
For microarray based techniques there exist many different types of normalizing methods directed at different sources of bias (e.g. dye effects or background noise).
A self-normalizing method is developed to eliminate the requirement of initial design process for normalization and improve diversity of the solution.
Only the Q normalization method, which is an appropriate method commonly used for normalizing microarray data [ 23, 24], exhibited any substantive differences.
Linear & LOWESS, which is the default normalization method in the Agilent Feature Extraction Software A.7.5.1, were applied for normalizing Agilent microarrays.
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