Facial expression recognition using deep learning techniques / Aznal Anas Azlan and Muhamad Arif Hashim

Azlan, Aznal Anas and Hashim, Muhamad Arif (2023) Facial expression recognition using deep learning techniques / Aznal Anas Azlan and Muhamad Arif Hashim. In: Research Exhibition in Mathematics and Computer Sciences (REMACS 5.0). College of Computing, Informatics and Media, UiTM Perlis, pp. 187-188. ISBN 978-629-97934-0-3

Abstract

Human’s feelings can be judged by their face expressions. Face expressions, in general, are a natural and direct way for humans to communicate their emotions and intentions. Trying to recognize the expression on a human face using devices is very difficult. Main objective of this research is to recognize several kinds of human face expression by implementing Convolutional Neural Network (CNN) technique in the facial expression recognition system. The system will display the result of the expression made by the user. The expressions that will be detected are “angry”, “disgusted”, “fearful”, “happy”, “neutral”, “sad”, and “surprised”. In conclusion, this research successfully developed a working facial expression recognition (FER) system with a high accuracy result.

Metadata

Item Type: Book Section
Creators:
Creators
Email / ID Num.
Azlan, Aznal Anas
UNSPECIFIED
Hashim, Muhamad Arif
UNSPECIFIED
Subjects: Q Science > QA Mathematics > Instruments and machines > Electronic Computers. Computer Science > Neural networks (Computer science)
Divisions: Universiti Teknologi MARA, Perlis > Arau Campus > Faculty of Computer and Mathematical Sciences
Page Range: pp. 187-188
Keywords: CNN, facial expression, FER system, emotion, artificial intelligence
Date: 2023
URI: https://ir.uitm.edu.my/id/eprint/100395
Edit Item
Edit Item

Download

[thumbnail of 100395.pdf] Text
100395.pdf

Download (1MB)

ID Number

100395

Indexing

Statistic

Statistic details