facial expression recognition; human emotion detection; naturalistic expression; recognition of emotional facial expressions; convolutional neural network, image processing, face detection
Abstract
Because of the heterogeneity present across human faces, recognising a human's facial expression with a computer is a difficult undertaking. This variability encompasses expression, color, position, and orientation.The purpose of this study is to demonstrate how a Convolution Neural Network (CNN) architecture may be utilised to detect facial expressions in real time. The FER 2013 Facial Expression Recognition Challenge dataset was employed in this study, and our neural network was trained to categorise emotion states using it. For the classification of seven different types of emotions using facial expressions, we attained an accuracy of 77.16 percent and a validation accuracy of 57.41 percent in this study.
Article Details
Unique Paper ID: 151801
Publication Volume & Issue: Volume 8, Issue 1
Page(s): 762 - 766
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