Table 5.

Classifiers for gender (G) classification and age (Ag) prediction. ‘*’ denotes that all of their algorithms used the approach. Numbers represent the algorithm numbers per team.

Team No.	Gender (G)/Age (Ag)	CNN	ConvLSTM	Bidirectional-LSTM	Conv. GRU DNN	ResNet-Based Net.	Temporal Conv. Network	Random Forest	K-Nearest Neighbor	Support Vector Machine	Support Vector Regressor	Random Subspace	XGboost Classifier	Support Vector Classifier	Sequential Minimal Optimization	KNN Regressor	Decision Tree Regressor	Ridge Regressor	Binary Age Tree	KStar	Ensemble Methods
T1	G	1
.	Ag	1
T2	G	2						*	*	*											*
.	Ag							*										2			*
T3	G	*																			4
.	Ag	*																			5–7
T4	G		1
.	Ag		1																1
T5	G	1, 2		1, 2	4	3, 4		3, 4													*
.	Ag			1, 2	4	3, 4		3, 4													*
T6	G			*
.	Ag			*
T7	G	6					3–6	1	1	2		1			1						7
.	Ag	6					3–6	1			2	1			1					1	7
T8	G									*
.	Ag										*
T9	G	2						1,3		1
.	Ag	2						1,3			1		3	3				3
T10	G							3	1	2
.	Ag										2					1	3