Face recognition has become a valuable and routine forensic tool used by criminal investigators. It is an important area of computer vision research and has gained significant interest in recent years. Efforts in improving security, such as automatic surveillance and the use of biometrics in identification, are partly responsible for this increased interest. However, several challenges remain i...

A new meta-heuristics is introduced here: the Multi-Particle Collision Algorithm (M-PCA). The M-PCA is based on the implementation of a function optimization algorithm driven for a collision process of multiple particles. A parallel version for the M-PCA is also described. The complexity for PCA, M-PCA, and a parallel implementation for the MPCA is developed. The efficiency for optimization for...

PCANet is an unsupervised Convolutional Neural Network (CNN), which uses Principal Component Analysis (PCA) to learn convolutional filters. One drawback of that linear PCA cannot capture nonlinear structures within data. To address this problem, a straightforward approach utilizing kernel methods by equipping the method in with function. However, practice leads network having cubic complexity r...

In probabilistic PCA, the fully Bayesian estimation is computationally intractable. To cope with this problem, two types of approximation schemes were introduced: the partially Bayesian PCA (PB-PCA) where only the latent variables are integrated out, and the variational Bayesian PCA (VB-PCA) where the loading vectors are also integrated out. The VB-PCA was proposed as an improved variant of PB-...

OBJECTIVE We aimed to show the relationship between paraoxonase 1 (PON1) gene polymorphism and the development of prostate cancer (PCa). MATERIAL AND METHODS We investigated the association of single nuclotide polymorphisms of PON1 enzyme with the development of PCa risk. A total of 147 male patients were divided into PCa, and control groups. The control group was also divided into two subgro...