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In other words, two new different sub-pattern based whitened PCA approaches (which are called Sp-PCA I and Sp-PCA II, respectively) were performed and compared with PCA I, PCA II, PCA, and sub-pattern based PCA (SpPCA).
Then, we find that sub-pattern technique is useful to PCA I but not to PCA II and PCA.
Therefore, in this paper, the sub-pattern technique was combined with PCA I and PCA II, respectively, for face recognition.
This means that the computationally expensive ICA projection is unnecessary for further process and involved PCA process of ICA, whether PCA I or II, can be used directly for face recognition.
Recently, in a task of face recognition, some researchers presented that independent component analysis (ICA) Architecture I involves a vertically centered principal component analysis (PCA) process (PCA I) and ICA Architecture II involves a whitened horizontally centered PCA process (PCA II).
The 13 factors extracted by PCA (i.e. 100% of information) were included in DA.
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The intracranial atherosclerotic lesions were localized mainly at PCA, I-ICA, ACA, MCA and the cervical atherosclerotic lesions were localized mainly at CCA. *Based on the rating of more affected side in case of bilateral vessel lesions.
At last, by simultaneously considering global and local information of face images, we developed a novel hybrid approach which combines PCA II and Sp-PCA I for face recognition.
Without PCAs, I would be stuck in bed and ultimately have to live in a nursing home.
Several reported loadings did not approach the minimal level recommended for PCAs (i.e.,.32, Tabachnick and Fidell 2007), and there was insufficient information provided about the cross-loadings.
A total of 108 staff will participate in the study, including 54 senior staff (i.e., 3 facility managers and/or RNs from each of the 18 facilities) and 54 senior PCAs (i.e., 3 PCAs from each of the 18 facilities).
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