. 2022 Mar 28;81(19):27737–27781. doi: 10.1007/s11042-022-12826-y

Table 11.

Hyper-parameters used in the study

Model	Batch Size	Loss function	Adam		T-Acc^*	SGD		T-Acc	RMSprop		T-Acc
Model	Batch Size	Loss function	Epochs	Learning Rate	T-Acc^*	Epochs	Learning Rate	T-Acc	Epochs	Learning Rate	T-Acc
VGG16	10	Categorical cross-entropy	5	0.0001	92.2	10	0.0001	88.9	5	0.0001	99.5
VGG19	10	Categorical cross-entropy	10	0.0001	99.1	10	0.0001	76.0	10	0.0001	99.3
DenseNet	10	Categorical cross-entropy	20	0.0001	83.0	20	0.0001	83.6	20	0.0001	96.8
Inception	10	Categorical cross-entropy	40	0.0001	94.0	30	0.0001	94.5	15	0.0001	98.5
Xception	10	Categorical cross-entropy	10	0.0001	60.5	20	0.0001	98.5	10	0.0001	98.9
Inception-ResNet-v2	10	Categorical cross-entropy	30	2e – 3	87.9	30	2e - 3	84.7	30	2e - 3	94.1
EfficientNetB0	10	Categorical cross-entropy	20	0.0001	98.3	20	0.0001	94.7	20	0.0001	93.2
EfficientNetB4	10	Categorical cross-entropy	20	0.0001	96.1	20	0.0001	94.2	20	0.0001	94.9

*T-Acc means Training Accuracy