Research Article
A facial expression recognizer using modified ResNet-152
@ARTICLE{10.4108/eetiot.v7i28.685, author={Wenle Xu and Rayan S Cloutier}, title={A facial expression recognizer using modified ResNet-152}, journal={EAI Endorsed Transactions on Internet of Things}, volume={7}, number={28}, publisher={EAI}, journal_a={IOT}, year={2022}, month={4}, keywords={Facial expression recognition, ResNet-152, Recognition system}, doi={10.4108/eetiot.v7i28.685} }- Wenle Xu
Rayan S Cloutier
Year: 2022
A facial expression recognizer using modified ResNet-152
IOT
EAI
DOI: 10.4108/eetiot.v7i28.685
Abstract
In this age of artificial intelligence, facial expression recognition is an essential pool to describe emotion and psychology. In recent studies, many researchers have not achieved satisfactory results. This paper proposed an expression recognition system based on ResNet-152. Statistical analysis showed our method achieved 96.44% accuracy. Comparative experiments show that the model is better than mainstream models. In addition, we briefly described the application of facial expression recognition technology in the IoT (Internet of things).
Copyright © 2022 Wenle Xu et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
