G. Sumalatha
Deep learning, Image processing, CNN, VGG-16, Transfer learning.
Automatic expression recognition based on facial expression is a fascinating study area that has been presented and utilized in a variety of fields, including safety, health, and human-machine interactions. Researchers in this subject are interested in developing strategies to understand, code, and extract facial expressions in order to improve computer prediction. Facial emotion recognition is a subset of facial recognition that is becoming in popular as the need for it grows. Though there are methods for identifying expressions using data science techniques like machine learning and deep learning, this work seeks to recognize expressions and classify them based on photographs utilizing deep learning and image classification methods. In this case we are going to use CK+48 dataset and going to build deep learning models. First we do image processing after doing image processing split the data in 80:20 or 70:30 ratio. By using train we train the model then test it on test data. In this paper we build CNN and VGG-16 model. The goal of this project based on images we need to predict face emotion. In this by using deep learning model we can predict with 98% accuracy.
Article Details
Unique Paper ID: 154371

Publication Volume & Issue: Volume 8, Issue 11

Page(s): 6 - 11
Article Preview & Download

Share This Article

Join our RMS

Conference Alert

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024

Last Date: 15th March 2024

Call For Paper

Volume 10 Issue 10

Last Date for paper submitting for March Issue is 25 June 2024

About Us

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org

Social Media

Google Verified Reviews