Fusion: Practice and Applications
FPA
2692-4048
2770-0070
10.54216/FPA
https://www.americaspg.com/journals/show/556
2018
2018
Identification of Facial Expressions using Deep Neural Networks
Information Technology Bharati Vidyapeeth's College of Engg, New Delhi, India
Harsh
Harsh
Information Technology Bharati Vidyapeeth's College of Engg, New Delhi, India
Parv
..
Information Technology Bharati Vidyapeeth's College of Engg, New Delhi, india;
Arun Kumar
Dubey
Information Technology Bharati Vidyapeeth's College of Engg, New Delhi, India
Preetika
Soni
Detecting and analyzing emotions from human facial movements is a problem defined and developed over many years for the benefits it brings. During playback, when developing data sets, data sets with methods become more and more complex, and accuracy and difficulty increase gradually. In the given paper, we will use a deep structured learned network using the two mechanisms - Vgg and Resnet50 with deep layers to classify emotions based on input images in complex environments. Besides that, we also use learning methods combining many modern models to increase accuracy. Experimental results show that the two proposed methods have better results than some modern methods in emotional recognition problems for complex input images and some results reported in scientific studies. Particularly combined learning method gives good accuracy - 66.15% on the dataset FER2013
2020
2020
22
30
10.54216/FPA.020101
https://www.americaspg.com/articleinfo/3/show/556