face recognition, convolutional neural network, softmax classifier, deep learning.
For real world applications like video surveillance, human machine interaction, and security systems, face recognition is of great importance. Deep learning based methods have shown better performance in terms of accuracy and speed of processing in image recognition compared to traditional machine learning methods. This paper presents a modified architecture of the Convolution Neural Network (CNN) by adding two operations of normalization to two of the layers. The operation of normalization that is normalization of the batch provided acceleration of the network. CNN architecture was used to extract distinctive facial characteristics and Softmax classifier was used to classify faces within CNN's fully connected layer. Our Face Database has shown in the experiment part that the proposed approach has improved the performance of face recognition with better results of recognition. Deep learning is an approach to perform the face recognition and seems to be an adequate method to carry out face recognition due to its high accuracy. Experimental results are provided to demonstrate the accuracy of the proposed face recognition system.
Article Details
Unique Paper ID: 162284

Publication Volume & Issue: Volume 10, Issue 9

Page(s): 74 - 80
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