Authors :
P. M. S. Bhargav Kumar, K.Yasudha
Volume/Issue :
Volume 5 - 2020, Issue 4 - April
Google Scholar :
http://bitly.ws/9nMw
Scribd :
https://bit.ly/3bPdUhh
Abstract :
Face recognition is essential for many
technologies around the world such as video
monitoring, interaction between human machines and
security systems. As per modern approaches to machine
learning, deep learning related techniques give excellent
results in terms of accuracy and processing speed in
image recognition. Face recognition recommends a
modified architecture of the Convolutional Neural
Network (CNN) by collecting two standardization
operations on 2 layers. The process of normalization
which is normalization by batch introduces acceleration
of the network. CNN architecture was used to remove
distinctive face features and Softmax classifier was used
to identify faces within fully connected layer of
Convolutional Neural Network
Keywords :
Face Recognition, Deep learning Algorithm, Convolutional Neural Network algorithm, Stacked Auto encoder.
Face recognition is essential for many
technologies around the world such as video
monitoring, interaction between human machines and
security systems. As per modern approaches to machine
learning, deep learning related techniques give excellent
results in terms of accuracy and processing speed in
image recognition. Face recognition recommends a
modified architecture of the Convolutional Neural
Network (CNN) by collecting two standardization
operations on 2 layers. The process of normalization
which is normalization by batch introduces acceleration
of the network. CNN architecture was used to remove
distinctive face features and Softmax classifier was used
to identify faces within fully connected layer of
Convolutional Neural Network
Keywords :
Face Recognition, Deep learning Algorithm, Convolutional Neural Network algorithm, Stacked Auto encoder.
