Face Recognition Using Deep Learning

Abstract

Today face recognition and its usage are  developing at a remarkable rate. Researches are at present building up different strategies in which facial recognition framework works. In circumstances like accidents, normal disasters, missing cases, clashes between nations, kidnappings and numerous different circumstances individuals are regularly isolated by their families. Recognizing the relatives of those refugees is essential to arrive at their family for refugee’s security and backing. Everyday polices are enrolling with missing cases, a portion of those enlisted cases are getting tackled and some are definitely not by using the manual method where it takes more time. The goal of this paper is to provide a solution to overcome time delay from existing strategies for police examination utilizing most recent innovation. Hence we adopt a framework which utilizes CNN (Convolutional Neural Network) technique with VGG16 architecture where we use our raw dataset which contains 84 images collected from 21 families data, after applying augmentation method the image count in final dataset is increased to 1512, then from this dataset 80% of data is used for training data and 20% is used for testing data. This framework helps to verify an individual’s trait using their face and family subtleties with related model with increased accuracy, and gives a effective solution for identifying refugee’s family.