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. 2024 Feb 29;10(5):e26938. doi: 10.1016/j.heliyon.2024.e26938

Table 2.

Model parameters setting for experimentation.

Parameters [31] vgg16 vgg19 EfficiebtnetB0 ResNet50 Hybrid Deep Learning Models
Image size 150 × 150 × 3 150 × 150 × 3 150 × 150 × 3 150 × 150 × 3 150 × 150 × 3
Batch size 64 64 64 64 64
Optimizer Adam Adam Adam Adam Adam
Learning rate 3e-4 3e-4 3e-4 3e-4 3e-4
epochs 25 25 25 25 25
1st Dense layer Activation Function(1000) Relu activation Relu activation Relu activation Relu activation Relu activation
2nd and 3rd Dense layer Activation Function(500,150) Sigmoid activation Sigmoid activation Sigmoid activation Sigmoid activation Sigmoid activation
Dropout 0.5 0.5 0.5 0.5 0.5
Output Layer(2) Categorical/Softmax Categorical/Softmax Categorical/Softmax Categorical/Softmax Categorical/Softmax
Activation/Loss Function Cross Entropy Cross Entropy Cross Entropy Cross Entropy Cross Entropy