A Systematic Approach to Face Recognition Using Convolutional Neural Network

Recently, deep learning has surpassed conventional artificial intelligence techniques in number of fields. Convolutional neural networks (CNNs) have shown promising results in facial recognition because convolutional neural networks (CNNs) can extract discriminative information, they have shown good performance in face recognition. In this research paper, thoroughly evaluated CNN-based facial recognition systems on a common platform to make work easily repeatable. The proposed CNN model is compared with other algorithms quantitatively in this article, and the impact of various implementation options is assessed. For experimentation here our proposed dataset of 4000 image datapoints is used. The results shows that our proposed model has outperformed majority of the state-of-the-art models with an accuracy rate of 97.50%,