Emotion Detection Using Machine Learning Technique
subject: Deep learning; Facial emotion recognition (FER); Facial expressions; Semi-supervised learning; Traditional classification methods
description: Face Emotion Recognition (FER) is an emerging and crucial topic today; since much research has been done in this field, there are still many things to explore. In daily life, where people dont have time to fill out feedback, emotion detection plays an important role, which helps to know customer feedback by analyzing expressions and gestures. Analyzing current studies in emotion recognition demonstrates notable advancements made possible by deep learning. A thorough overview of facial emotion recognition (FER) is provided in this publication. The literature cited in this study is taken from various credible research published in the last 10years. This study has built a model for emotion recognition using photos or a camera. The paper is based on the concepts of Machine Learning (ML), Deep Learning (DL), and Neural Networks (NN). A range of publicly available datasets have been used to evaluate evaluation metrics. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
creator: Shukla S.; Lucas Y.
source: Lecture Notes in Networks and Systems, Vol-922 LNNS, pp. 547-557.
publisher: Springer Science and Business Media Deutschland GmbH
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 23673370; ISBN: 978-981970974-8
format: Online
language: English
type: Conference paper
coverage: Shukla S., Christ University, Bengaluru, India; Lucas Y., Christ University, Bengaluru, India