RETRACTED: Facial Recognition Using Aggregation and Random Forest Classification Method

Abstract

Face detection and recognition performs an essential role in computer. There was tremendous increase in face recognition during the last years. There are numerous applications that require the face detection. As this face detection is the first step. There are many growing applications such as bank authentication, security access in system, enforcement of law, verification of credit cards, biometric authentication which works based on face detection. The goal of this paper is to presents a facial recognition system with deep learning methodologies. In this paper machine learning aggregation method is used to store the feature of detecting image and random forest algorithm also used to classify a detected image which is applied on face database and compared with previous algorithm which shows accurate ratio.

The Overview of Database Security Threats’ Solutions: Traditional and Machine Learning

“…The author improved CNN by adding standard operation between input layer and output layer, the improvement could accelerate network standardization, but there was a problem of over-fitting in face recognition. Aishwarya et al [46] utilized aggregation and RF (Random Forest) to improve face recognition rate. RF introduces random attribute selection in the training process of decision tree [47].…”