The optically modified fraction profile includes the contribution of optical parameters (excitation and beer-Lambert law with zirconia optical parameters) to the real transformation profile described in Eq. (2).
This means that the real transformation profile (F z)) can be determined precisely directly from the simulation of the AF z) curve and the fit of the experimental AF z) curve.
To proceed with the LOOLP, 199 individuals are used to learn the CCA transformation frontal-profile (estimate w x, w y ) and the remaining individual of the profiles set together with the frontal faces of the test set are projected onto the canonical space using w y and w x, respectively, for comparison.
Evaluation of our approach according to the leave one out-like protocol (LOOLP), 199 individuals are used to learn the CCA transformation frontal-profile (estimate w x, w y ) and the remaining individual of the profiles set together with the frontal faces of the test set are projected onto the canonical space using w y and w x, respectively, for comparison.
In each iteration, m−1 faces (from both datasets) are used to learn the CCA transformation frontal-profile.
The transformation between profile face image (90° angle pose) and frontal face image (0° angle pose) is known to be nonlinear, and this nonlinearity is taken into account by introducing kernel functions.
After this transformation, each profile b r sums to one, allowing them to be interpreted as a discrete probability distribution over transcripts.
Since we have proved that the abstract form of our CKE models is invariant by arbitrary multiple affine transformations of profiles data, we have made sure to constrain the distance of two expression levels profiles to be invariant by these types of affine transformations.
For the other model based on PSSM (PSSM-b), initially different lg values ranging from 5 to 40 were tried for Auto-Cross Covariance (ACC) transformation of PSSM profiles but the optimal lg (on the basis of highest accuracy) was obtained as 15.
This leads to the prediction of real transformation factors and profiles for any aging times without any mechanical sectionning which could induce some additional degradations.
