Ear Biometrics Using Deep Learning: A Survey

Table 2

Summary of the deep convolutional neural network architecture used for ear identification.

Deep convolutional neural network architecture	Summary of deep convolutional neural network used in ear identification	Accuracy (%)
AlexNet [11]	AlexNet is seen as a deep convolutional neural network architecture and applied to numerous ear recognition systems	53.6
DenseNet [16]	DenseNet connects each layer in the CNN to another and applied to ear image datasets, yielding positive results	62.0
ResNet [14]	ResNet is a class of extremely deep CNN architecture that addresses vanishing gradient by using skip connections that prevent information loss as the network goes deeper. As ResNet addressed the vanishing gradient issue, it has been applied to numerous ear image datasets yielding positive results	15.0
ResNeXt [15]	ResNeXt is a modularised CNN architecture, which has been applied to ear image datasets yielding positive results	95.8
Visual geometry group [12]	The visual geometry group is a very deep CNN and is one of the top performers. The VGG is used in recognition systems and has been applied to unconstrained ear image datasets, yielding positive results.	83.0