USK-FEMO: A Face Emotion Dataset using Deep Learning for Effective Learning

Muhajir Muhajir, Maulisa Oktiana, Kahlil Muchtar, Maya Fitria, Akhyar Akhyar, Muhammad Dandy Pratama, Chih Yang Lin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Emotions play an essential role in the learning process and have an impact on how the learning process is eventually carried out. Facial expressions can be used to visually identify a person's emotions. Along with the advancement of computer vision and deep learning techniques, the study of human-computer interaction is increasingly focusing on the recognition of facial expressions. One of the main issues is the availability of sufficient datasets, especially for students. This study examined the deep learning architecture for face emotion classification. In addition, this research also introduces a new emotional dataset acquired from the junior high school student at SMP Negeri 1 Darul Imarah, Aceh Besar Regency, Indonesia. This dataset contains five classes that include the emotions of happiness, sadness, anger, surprise, and boredom. The dataset was then tested using the Mobile-Net architecture, the highest accuracy was achieved with a learning rate of 0.0001% of 88.492%. %. The dataset can be explored via the link https://muhajir2111.github.io/USK-FEMO-DATASET/.

Original languageEnglish
Title of host publicationProceeding - 2023 2nd International Conference on Computer System, Information Technology, and Electrical Engineering
Subtitle of host publicationSustainable Development for Smart Innovation System, COSITE 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages199-203
Number of pages5
ISBN (Electronic)9798350343069
DOIs
StatePublished - 2023
Event2nd International Conference on Computer System, Information Technology, and Electrical Engineering, COSITE 2023 - Banda Aceh, Indonesia
Duration: 2 Aug 20233 Aug 2023

Publication series

NameProceeding - 2023 2nd International Conference on Computer System, Information Technology, and Electrical Engineering: Sustainable Development for Smart Innovation System, COSITE 2023

Conference

Conference2nd International Conference on Computer System, Information Technology, and Electrical Engineering, COSITE 2023
Country/TerritoryIndonesia
CityBanda Aceh
Period2/08/233/08/23

Keywords

  • Deep Learning
  • Emotion Classification
  • Emotion Dataset
  • Mobile-Net architecture

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