Abstract
Facial expression recognition is the part of Facial recognition which is gaining more importance and need for it increases tremendously. Though there are methods to identify expressions using machine learning and Artificial Intelligence techniques, this work attempts to use deep learning and image classification method to recognize expressions and classify the expressions according to the images. Various datasets are investigated and explored for training expression recognition model are explained in this paper. Inception Net is used for expression recognition with Kaggle (Facial Expression Recognition Challenge) and Karolinska Directed Emotional Faces datasets. Final accuracy of this expression recognition model using Inception Net v3 Model is 35%(~).
Publisher
Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP
Subject
Computer Science Applications,General Engineering,Environmental Engineering
Cited by
13 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. A Survey on Facial Emotion Recognition (FER) using Machine Learning and Deep Learning Methods;International Journal of Advanced Research in Science, Communication and Technology;2024-08-01
2. Performance Analysis of Child Emotion Detection using Haar Cascade and CNN;International Journal of Engineering and Advanced Technology;2024-04-30
3. Emotional detection system using machine learning;AIP Conference Proceedings;2024
4. Emotion Detection for the Blind Using Deep Learning;Lecture Notes in Networks and Systems;2024
5. Understanding Facial Expression of Children with Autism Using Learning Theory;2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE);2023-12-04