Conversely, the sign based method tries to detect and describe the relative positions and shapes of the main facial components, such as eyes, brows, and mouth, while leaving the interpretation of the shown expression to a high level of decision making[17].
Optimization-based methods try to find the best assignment of disparities by minimizing an energy function.
Unlike MSE or PSNR, the HVS property-based methods try to construct a mathematic model to simulate HVS characteristics, including visual masking effect [6], contrast [7], and just noticeable differences [8].
In short, frequency-based methods try to exploit the fact that mutations under positive Darwinian selection fix in the population with a higher rate than neutral or deleterious mutations.
Prediction/classification-based methods try to find the best set of SNPs, which can generate the highest prediction/classification accuracy including, for example, multifactor dimensionality reduction (MDR) [ 4], penalized logistic regression (e.g., stepPLR [ 5], and lassoPLR [ 6]), support vector machine (SVM) [ 7], and random forest [ 8].
Approaches based on bioinformatics methods try to predict the fold-change in resistance from genotype [13], [14].
This research, which was based on momentum method, tries to find the influence of different flow patterns on the temperature distribution and capture the flow patterns' picture as reference.
The proposed method tries to mitigate this phenomenon by using reference profiles, whose calculation is based on the previously aligned range profiles.
