A Comprehensive Analyze of Deep Learning Techniques and Applications

Shuo Song

2025

Abstract

Facial emotion recognition (FER) is a key research direction in the field of artificial intelligence and human-computer interaction (HCI). This technology is of great significance for improving the emotion understanding ability of virtual reality, intelligent customer service, intelligent driving and other systems. Currently, deep learning models can significantly improve the recognition accuracy of FER, which makes up for the limitation that traditional methods are difficult to cope with complex and changing real-world scenarios. This paper systematically reviews the development history of FER, and analyzes its typical applications in human-computer interaction from the perspectives of both traditional methods and deep learning methods. In summary, it is found that deep learning methods have made significant progress in multimodal emotion recognition, real-time performance optimization, and personalized modeling, but still face challenges such as data imbalance, occlusion interference and cross-domain adaptability. This paper provides an outlook on the future development trend of FER, aiming to provide reference and inspiration for subsequent research.

Paper Citation

in Harvard Style

Song S. (2025). A Comprehensive Analyze of Deep Learning Techniques and Applications. In Proceedings of the 2nd International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI; ISBN 978-989-758-792-4, SciTePress, pages 589-593. DOI: 10.5220/0014366900004718

in Bibtex Style

@conference{emiti25,
author={Shuo Song},
title={A Comprehensive Analyze of Deep Learning Techniques and Applications},
booktitle={Proceedings of the 2nd International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI},
year={2025},
pages={589-593},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0014366900004718},
isbn={978-989-758-792-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI
TI - A Comprehensive Analyze of Deep Learning Techniques and Applications
SN - 978-989-758-792-4
AU - Song S.
PY - 2025
SP - 589
EP - 593
DO - 10.5220/0014366900004718
PB - SciTePress