MACHINE LEARNING FOR FACIAL RECOGNITION: A REVIEW OF TECHNIQUES AND APPLICATIONS

The field of facial recognition has gained widespread interest due to its potential to be used in various applications, such as security and law enforcement. Machine learning techniques are commonly used to develop such systems, which are capable of identifying individuals based on their facial features. The literature review aims to provide an overview of the ten studies that investigated the use of machine learning in facial recognition. It also summarizes the various aspects of the research, including the techniques used, the image groups utilized, the accuracy results, and the findings. The literature review focuses on the various aspects of the research that were conducted in the field of facial recognition. Some of these include the use of patch-based methods for face selection, the development of facial expression recognition systems with matched background features, and the use of histograms of Oriented gradients. In addition, it analyzed the various techniques that were used in deep face recognition. The review provides an overview of the various developments that have occurred in the field of machine learning. It also discussed the implications of these technologies for society and the industry. It also analyzed the ethical and privacy concerns that are raised by the use of such systems.