A Comprehensive Review of Face Detection Using Machine Learning and Deep Learning Approaches

Today, biometric systems are used in analyzing and verifying the unique physical or behavioral attributes of a person for authentication purposes or to be recognized. This is done to ensure that the person in question is indeed who he or she claims to be. Face recognition-based systems are the highest popular choice since they independent on user help every now and then; this had become more automated besides being easy for them to be operated. Many authentication systems up to now have used Iris, fingerprints and facial features. These systems have been utilized in the process of identification and verifications. One the other hand, people prefer face recognition-based system among these systems. This review paper conducts comparison and contrast of various face recognition methods along with hybrid combinations. The hybrid combinations are also compared in the review paper. Furthermore, the most frequently used datasets in this field are analyzed and reviewed. Apart from that, this paper argues the different facial recognition algorithms inspired by DL and also touched on what opportunities exist in this field in future along with some obstacles expected to be present.