TABLE 1.

Training options for different pre‐trained models

Training options (random initialization weights, batch size = 32, learning rate = 0.00001 and number of epochs = 10)
Model	Input size	No. of layers
AlexNet (Simonyan & Zisserman, 2014)	227 × 227	8
GoogleNet (Ballester & Araujo, 2016)	224 × 224	22
InceptionV3 (Parente & Ferreira, 2018)	299 × 299	48
InceptionresNetV2 (Alom et al., 2017)	299 × 299	164
SqueezeNet (Pradeep et al., 2018)	227 × 227	18
DenseNet201 (Haupt et al., 2018)	224 × 224	201
ResNet18 (Wu et al., 2019)	224 × 224	18
ResNet50 (Alom et al., 2018)	224 × 224	50
ResNet101 (Ghosal et al., 2019)	224 × 224	101
VGG16 (Zu et al., 2020)	224 × 224	16
VGG19 (Qassim et al., 2018)	224 × 224	19