Facial Emotion Recognition and Impact Analysis of Iteration Based on Convolutional Neural Networks

Anna Li

2023

Abstract

Many disciplines, including AI, psychology, and computer science, see considerable value in the ability to recognize human facial expressions. The primary goal of this research is to analyze the performance of the original Convolutional neural networks (CNN) model by examining how alternative CNN models perform in facial expression recognition under varying iteration cycles. This approach recognizes the intricate relationships between macro and micro expressions to present a more complete picture of the wide range of human emotions conveyed through facial expressions. A key takeaway from the experiments is that with repeated iterations, the model becomes increasingly accurate. This approach to facial emotion detection exemplifies the feasibility of combining various neural network architectures, allowing people to delve even deeper into the nuances of human emotion. Therefore, this research has made major contributions to the field of facial expression recognition by displaying the effectiveness of incorporating multi-scale feature extraction technologies to enhance the performance of the model. This study establishes the groundwork for future research avenues in the area and enables the development of more sophisticated emotion recognition algorithms for practical implementations.

Paper Citation

in Harvard Style

Li A. (2023). Facial Emotion Recognition and Impact Analysis of Iteration Based on Convolutional Neural Networks. In Proceedings of the 1st International Conference on Data Analysis and Machine Learning - Volume 1: DAML; ISBN 978-989-758-705-4, SciTePress, pages 5-9. DOI: 10.5220/0012799000003885

in Bibtex Style

@conference{daml23,
author={Anna Li},
title={Facial Emotion Recognition and Impact Analysis of Iteration Based on Convolutional Neural Networks},
booktitle={Proceedings of the 1st International Conference on Data Analysis and Machine Learning - Volume 1: DAML},
year={2023},
pages={5-9},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012799000003885},
isbn={978-989-758-705-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Data Analysis and Machine Learning - Volume 1: DAML
TI - Facial Emotion Recognition and Impact Analysis of Iteration Based on Convolutional Neural Networks
SN - 978-989-758-705-4
AU - Li A.
PY - 2023
SP - 5
EP - 9
DO - 10.5220/0012799000003885
PB - SciTePress