Table 3.

The accuracy of the proposed method is compared with the existing methods on the SEED-IV dataset.

Model	ACC (%)	STD (%)
SVM (Zhong et al., 2020)	56.61	20.05
DBN (Zhong et al., 2020)	66.77	7.38
GSCCA (Zheng, 2017)	69.08	16.66
DGCNN(Zhong et al., 2020)	69.88	16.29
BiDANN (Li Y. et al., 2018)	70.29	12.63
EmotionMeter (Zheng et al., 2018)	70.58	17.01
BiHDM (Li et al., 2020)	74.35	14.09
RGNN (Zhong et al., 2020)	79.37	10.54
SST-EmotionNet (Jia et al., 2020)	84.92	6.66
MDGCN-SRCNN	85.52	11.58

Bold represents the best result.