Table 3.

Description of facial recognition algorithms.

Facial recognition algorithm	Description of algorithm	Citation
VGG-Face	A model that uses a deep CNN with 22 layers and 37 deep units that converts faces into feature vector representations and employs a triplet loss function to make them generalizable	Parkhi et al.34
FaceNet	A deep CNN model built by Google based on the inception model that uses a triple-based loss function to directly create 128D embeddings; similar to VGG-Face, the model represents the images as small dimension vectors and uses similarity to determine the identification	Schroff et al.35
DLib	A CNN model with a ResNet-34 network with built convolution layers that uses a facial map created by HOG to generate 128D vectors and checks similarity for facial recognition	King36
SFace	A CNN model that uses a loss function called sigmoid-constrained hypersphere loss that imposes intraclass and interclass constraints on a hypersphere manifold that allows for better balance between underfitting and overfitting, further improving generalizability of deep face models	Zhong et al.37