Authors :
G Mohan Sai; B Olive Noel; B Lakshman Sai Kiran; B Karthik Krishna
Volume/Issue :
Volume 8 - 2023, Issue 10 - October
Google Scholar :
https://tinyurl.com/yc5j73p2
Scribd :
https://tinyurl.com/2p9hpy86
DOI :
https://doi.org/10.5281/zenodo.10071290
Abstract :
In this day and age, communicating emotions
through words alone might be difficult. Convolutional
Neural Networks (CNN), a sophisticated deep learning
algorithm, is used in this research to recognize human
facial expressions and improve communicating by
automatically recommending emojis that match the
displayed emotions, such as happiness, sorrow, anger,
and more. Our technology recognizes facial emotions in
photos in real time by combining computer vision and
deep learning. It then suggests appropriate emoticons to
go along with their words, making online discussions
more engaging and expressive. This project seeks to bring
brightness and complexity to the digital conversational
experience, eventually producing a more colorful and
expressive chat environment, rather than just solving a
problem.
Keywords :
CNN (Convolutional Neural Network), Deep Learning, Emotions.
In this day and age, communicating emotions
through words alone might be difficult. Convolutional
Neural Networks (CNN), a sophisticated deep learning
algorithm, is used in this research to recognize human
facial expressions and improve communicating by
automatically recommending emojis that match the
displayed emotions, such as happiness, sorrow, anger,
and more. Our technology recognizes facial emotions in
photos in real time by combining computer vision and
deep learning. It then suggests appropriate emoticons to
go along with their words, making online discussions
more engaging and expressive. This project seeks to bring
brightness and complexity to the digital conversational
experience, eventually producing a more colorful and
expressive chat environment, rather than just solving a
problem.
Keywords :
CNN (Convolutional Neural Network), Deep Learning, Emotions.
