# Facial Emotion Recognition Analysis Based on Age-Biased Data
## 4 Conclusions  
In this study, when recognizing facial expressions using the CNN algorithm, an accuracy improvement system based on solving the age bias problem of data was proposed. We provided a performance comparison of three CNN architectures in emotional recognition. Using the adopted architecture, we compared the performance of the age-specific learning model and the non-age-specific learning model. In the age-specific learning model, the recognition performance of each emotion of adults and kids was compared. In addition, the emotional deviations of adults and kids were compared. The framework proposed in the results of this study was able to obtain higher accuracy than the existing classifier in FER2013 and MMA FACIAL EXPRESSION. Although some of the previous studies outperformed our model in accuracy, the method had a much higher elapsed time. Based on the results of this study, the following conclusions can be drawn. 1. Based on the CNN algorithm, emotion recognition accuracy was derived using three types of architecture, and the accuracy of the architecture was verified through comparison with the object recognition benchmark chart. 2. When the data were trained by age, the average accuracy was 22% higher than that of the non-age-specific learning model. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Architecture** & \multicolumn{3}{c}{**MobileNet-V2**} & \multicolumn{3}{c}{**SE-ResNeXt50 (32 \(\times\) 4 d)**} & \multicolumn{3}{c}{**ResNeXt101 (64 \(\times\) 4 d)**} \\ \hline
**Dataset** & **Age-Specific** & **FER2013** & **MMA** & **Age-Specific** & **FER2013** & **MMA** & **Age-Specific** & **FER2013** & **MMA** \\ \hline Accuracy (\%) & 71.06 & 59.70 & 54.65 & 79.42 & 62.29 & 62.87 & 72.27 & 58.33 & 60.76 \\ Recall (\%) & 71.00 & 58.19 & 54.40 & 76.93 & 59.86 & 52.66 & 66.31 & 56.54 & 49.59 \\ Precision (\%) & 70.84 & 56.88 & 47.92 & 77.73 & 61.02 & 57.41 & 67.69 & 55.12 & 56.14 \\ F1 score (\%) & 70.19 & 57.25 & 48.86 & 76.93 & 59.43 & 53.98 & 66.03 & 55.38 & 51.08 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Comparison of our dataset and the existing dataset of each architecture. Figure 9: Accuracy deviation between age-specific and nonage-specific of SE-ResNeXt50 (32 \(\times\) 4 d): (**a**) deviation between the age-specific and opposite-age groups, (**b**) deviation between the age-specific and mixed-age groups. 3. In the case of the adult learning model, it was difficult to recognize the emotions of angry, fear, and sad. In the case of the kid learning model, only the fear emotion was derived with low accuracy. 4. The age-specific learning model and the mixed learning model also achieved up to 32.70% improvement in the recognition accuracy of the fear emotion. The above results prove the importance of the age bias problem in emotional recognition. They also show the need for pre-processing the learning model according to age and emotion. This study provides comparative data for emotion and age to researchers in the field of emotion recognition and proposes insight into the age bias problem experienced in emotion recognition learning models. In our future work, data processing or emotion recognition architecture will be developed to improve the accuracy of specific emotions for which there is low accuracy by age. Conceptualization, H.P. and Y.S. ; methodology, H.P., Y.S. and K.S. ; software, H.P. ; validation, D.J., K.S. and C.Y. ; formal analysis, H.P. ; investigation, D.J. ; resources, D.J. ; data curation, H.P. ; writing--original draft preparation, H.P. and Y.S. ; writing--review and editing, D.J., K.S. and C.Y. ; visualization, H.P. and Y.S. ; supervision, D.J. ; project administration, D.J. ; funding acquisition, D.J. All authors have read and agreed to the published version of the manuscript. This study is a research project conducted with the support of the Ministry of SMEs and Startups with funds from the Ministry of Trade, Industry, and Energy (No. S2640869). Not applicable. The data presented in this study are available on request from the corresponding author.