Resetting Threshold Values for Improving Facial Expression Recognition Accuracy
Ryo Kiyokawa, Masaki Ishii, Yoichi Kageyama · 2020 IEEE 2nd Global Conference on Life Sciences and Technologies (LifeTech) · 2020
When facial expression recognition is performed using a counter propagation network and fuzzy adaptive resonance theory, additional facial expression pattern learning is also performed based on the feature space of facial expression generated by the initial learning. It is necessary to carefully judge whether or not to perform this additional learning. In this study, appropriate provisional threshold values were investigated for this purpose.