A facial expression recognizer using modified ResNet-152
Wenle Xu, Rayan S Cloutier
EAI Endorsed Transactions on Internet of Things · 2022
doi:10.4108/eetiot.v7i28.685 (opens in a new tab)
We email you when a new notice or a question about this paper appears.
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).
Abstract licence: CC BY-NC-SA
Reads
Read by people on this page
None yet.
Checked or read by AI through naulon
None yet.
A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.
Are you an author?
Is this your paper?
Claim it to add your note and be paid when agents cite it. Free.