Table 2.

Performance metrics (standard deviation as subscript) achieved by ResNet of each feature type on the DiveFace dataset

	FA	FB	FC	MA	MB	MC	Average
(a) Accuracy
SI	$88.{89}_{0.40}$	$92.{90}_{0.56}$	$96.{56}_{0.34}$	$90.{66}_{0.67}$	$95.{50}_{0.42}$	$97.{39}_{0.26}$	$93.{65}_{0.44}$
GD	$96.{44}_{0.37}$	$95.{52}_{0.40}$	$97.{07}_{0.44}$	$95.{83}_{0.49}$	$95.{63}_{0.20}$	$96.{75}_{0.28}$	$96.{21}_{0.36}$
GED	$\mathbf{98}.{\mathbf{38}}_{\mathbf{0.28}}$	$\mathbf{97}.{\mathbf{24}}_{\mathbf{0.33}}$	$\mathbf{98}.{\mathbf{68}}_{\mathbf{0.24}}$	$\mathbf{97}.{\mathbf{72}}_{\mathbf{0.27}}$	$\mathbf{97}.{\mathbf{09}}_{\mathbf{0.30}}$	$\mathbf{98}.{\mathbf{11}}_{\mathbf{0.16}}$	$\mathbf{97}.{\mathbf{87}}_{\mathbf{0.26}}$
(b) AUC
SI	$98.{29}_{0.40}$	$96.{76}_{0.35}$	$98.{46}_{0.25}$	$98.{50}_{0.29}$	$96.{96}_{0.24}$	$98.{27}_{0.32}$	$97.{87}_{0.31}$
GD	$99.{33}_{0.23}$	$98.{54}_{0.19}$	$99.{36}_{0.15}$	$99.{17}_{0.20}$	$98.{79}_{0.20}$	$99.{05}_{0.20}$	$99.{04}_{0.20}$
GED	$\mathbf{99}.{\mathbf{64}}_{\mathbf{0.18}}$	$\mathbf{99}.{\mathbf{10}}_{\mathbf{0.28}}$	$\mathbf{99}.{\mathbf{67}}_{\mathbf{0.15}}$	$\mathbf{99}.{\mathbf{54}}_{\mathbf{0.14}}$	$\mathbf{99}.{\mathbf{24}}_{\mathbf{0.24}}$	$\mathbf{99}.{\mathbf{55}}_{\mathbf{0.11}}$	$\mathbf{99}.{\mathbf{45}}_{\mathbf{0.18}}$

FA = Female-Asian, FB = Female-Black, FC = Female Caucasian, MA = Male-Asian, MB = Male-Black, and MC = Male Caucasian