An adaptive approach for Human Emotions Recognition System for Neural Networks using Hidden Markov Model and Self Organizing Maps algorithms

Azaraffali, K.M. and Krishnakumar, Dr.T. and Sriram, Dr.M. (2021) An adaptive approach for Human Emotions Recognition System for Neural Networks using Hidden Markov Model and Self Organizing Maps algorithms. In: I3CAC 2021, 7-8 June 2021, Bharath University, Chennai, India.

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Abstract

In machine learning, recognition of human emotions by a machine is an important research area. It is informal to reason of emotions as a luxury, approximately that is needless for basic intelligent operative, and something that is problematic to encode in a computer program. Then giving expressivecapabilities to machine has been a least priority up till now. But recent studies suggest that emotions play surprisingly dangerous role in balanced and brainybehavior. Too slightfeeling can damagebalancedthoughtful and behaviour. The main impartial of this paper is the identification of emotional states of human beings.Inthis researchthe algorithms to be used are Hidden Markov Model and Self Organizing Maps..

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: markov model self organizing maps algorithms neural networks human emotions recognition system
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
QA75 Electronic computers. Computer science
Depositing User: EAI Editor IV
Date Deposited: 21 Jun 2021 08:10
Last Modified: 21 Jun 2021 08:10
URI: https://eprints.eudl.eu/id/eprint/3893

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