Determining Real-Time Emotion Using Convolutional Neural Networks in Machine Learning

Ruby Gupta; V.K.Panchal; Saoud Sarwar

Author(s)

Ruby Gupta Department Of Computer Science & Engineering, Al-Falah University, Village Dhauj, Faridabad, Haryana India

V.K.Panchal Department Of Computer Science & Engineering, Al-Falah University, Village Dhauj, Faridabad, Haryana India

Saoud Sarwar Department Of Computer Science & Engineering, Al-Falah University, Village Dhauj, Faridabad, Haryana India

Abstract

This cutting-edge research project focuses on the development of a real-time emotion recognition system leveraging the power of Convolutional Neural Networks (CNNs) in the field of machine learning. Emotions play a pivotal role in human communication and behavior, and this project aims to create a system that can accurately and swiftly detect emotions from various sources, such as images, videos, or audio data. The recognition of human emotions is a captivating and multidisciplinary field that explores the intricate tapestry of human feelings, encompassing psychology, neuroscience, computer science, and more. Emotions, being integral to our existence, influence our thoughts, actions, and relationships. This pursuit involves deciphering emotional cues from various sources, including facial expressions, vocal intonations, physiological responses, and textual content. The identification of human emotions has been extensively studied, but there are no effective techniques that can identify them correctly. In order to overcome this problem, the proposed method implements a real-time emotion recognition system by using machine learning. Convolutional neural networks (CNN) are used for both gender and emotion classification.

Publication Details

Page(s) 1098-1108

DOI DOI not available

Published Journal: International Journal of Communication Networks and Information Security, Volume: 16, Issue: S1, Year: 2024

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Keywords

Emotion, segmentation, Human, recognition, Expressions

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