Advancements in Facial Expression-Based Automatic Emotion Identification Using Deep Learning

Clicks: 1
ID: 313191
2023
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal

Ranked #608 of 705 articles by views in Journal of Computing & Biomedical Informatics

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 705 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Facial expression-based automatic emotion identification is an intriguing research subject that has found applications in areas as diverse as security, healthcare, and the human-computer interface. Researchers in this area seek to improve computer prediction by creating methods for reading and encoding facial emotions. As deep learning has shown to be so effective, many designs have been used to maximize its potential. This paper's goal is to examine recent efforts towards fully autonomous FER with the use of deep learning. The researcher emphasizes these processing contributions, architectures and databases, and then illustrate the progress accomplished by comparing the offered approaches and acquired outcomes. This paper’s goal is to aid and direct scholars by surveying current efforts and offering suggestions for how to further the area.
Reference Key
imported_1777059682_69ebc762cdd99 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Nadeem Iqbal Kajla
Journal Journal of Computing & Biomedical Informatics
Year 2023
DOI
DOI not found
URL
https://jcbi.org/index.php/Main/article/view/183
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.