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.
