A Survey Paper on Emotion based Age Separated Customer Feedback System using CNN


Authors : Nighila Abish; Jesly Wilson; Ajo Thomas; Liliya Sujo; Noel Tony

Volume/Issue : Volume 8 - 2023, Issue 4 - April

Google Scholar : https://bit.ly/3TmGbDi

Scribd : https://bit.ly/3LzGWGT

Abstract : Humans use their emotions to express their feelings. There are numerous methods for people to communicate their feelings, including through body language and facial expressions. The most potent and common way for people to express their emotions through facial expression. CNN and a deep learningbased approach are both used in this work. Our goal is to built an emotion-based age-separated customer feedback system that enables businesses to improve their operations by better understanding the needs of customers of all ages. In this paper, we primarily examined the prior literature that has been published on emotion analysis in an effort to identify knowledge gaps and potential directions for future research.

Keywords : CNN, Customer Feedback, Age-Separate, Emotion Recognition, Machine Learning, Deep Learning.

Humans use their emotions to express their feelings. There are numerous methods for people to communicate their feelings, including through body language and facial expressions. The most potent and common way for people to express their emotions through facial expression. CNN and a deep learningbased approach are both used in this work. Our goal is to built an emotion-based age-separated customer feedback system that enables businesses to improve their operations by better understanding the needs of customers of all ages. In this paper, we primarily examined the prior literature that has been published on emotion analysis in an effort to identify knowledge gaps and potential directions for future research.

Keywords : CNN, Customer Feedback, Age-Separate, Emotion Recognition, Machine Learning, Deep Learning.

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