Support Vector Machine (SVM) is one of the most efficient machine learning algorithms,
which is mostly used for pattern recognition since its introduction in 1990s. SVMs vast variety …

Purpose Risk assessments have been constructed using a variety of algorithms, from
bivariate associations, to regression, to advanced machine learning (ML) approaches. While …

The growing interest in the credit industry resulted in credit scoring being developed as an
essential component, especially in the credit department of banks that deals with huge sums …

Pattern recognition techniques are divided into categories of supervised, unsupervised and
semi supervised. Supervised pattern recognition methods are utilized in the examination of …

Presently, the difficulty in managing illumination over the face recognition techniques and
smooth filters has emerged as one of the biggest challenges. This is due to differences …

Rapid growth of internet made sharing and distribution of media files became easier. This
phenomena and this fact that internet is boundary less network, raised the concern of …

The purpose of this review paper is to present the technical basis for establishing the quality
criteria by using the face recognition techniques and smooth filters. The metamorphoses in …

Face recognition under varying illumination is one of the challenging problems in real-time
applications. Numerous methods have been developed by the research community to …

Facial Recognition is integral to numerous modern applications, such as security systems,
social media platforms, and augmented reality apps. The success of these systems heavily …

One of the greatest challenges in facial recognition systems is to recognize faces around
different race and illuminations. Chromaticity is an essential factor in facial recognition and …