Table 5 Transfer learning model incorporating ResNet-50, ResNet-101, and EfficientNet-B3 with the specified configurations
Layer (type) | Output Shape | Param # | Connected to |
|---|---|---|---|
input_image (InputLayer) | (224, 224, 3) | 0 | – |
resnet50_base (Functional) | (7, 7, 2048) | 23,587,712 | input_image[0][0] |
resnet101_base (Functional) | (7, 7, 2048) | 42,658,176 | input_image[0][0] |
efficientnetb3_base (Functional) | (7, 7, 1536) | 10,783,535 | input_image[0][0] |
global_average_pooling2d | Global (2048) | 0 | resnet50_base[0][0] |
global_average_pooling 2d_1 | Global (2048) | 0 | resnet101_base[0][0] |
global_average_pooling2d_2 | Global (1536) | 0 | efficientnetb3_base[0][0] |
dense_layer_1 (Dense) | (128) | 262,272 | global_average_pooling2d[0][0] |
dense_layer_3 (Dense) | (128) | 262,272 | global_average_pooling2d_1[0][0] |
dense_layer_5 (Dense) | (128) | 196,736 | global_average_pooling2d_2[0][0] |
dropout_1 (Dropout) | (128) | 0 | dense_layer_1[0][0] |
dropout_3 (Dropout) | (128) | 0 | dense_layer_3[0][0] |
dropout_5 (Dropout) | (128) | 0 | dense_layer_5[0][0] |
dense_layer_2 (Dense) | (64) | 8256 | dropout_1[0][0] |
dense_layer_4 (Dense) | (64) | 8256 | dropout_3[0][0] |
dense_layer_6 (Dense) | (64) | 8256 | dropout_5[0][0] |
dropout_2 (Dropout) | (64) | 0 | dense_layer_2[0][0] |
dropout_4 (Dropout) | (64) | 0 | dense_layer_4[0][0] |
dropout_6 (Dropout) | (64) | 0 | dense_layer_6[0][0] |
output_layer (Dense) | (4) | 260 | dropout_2[0][0] dropout_4[0][0] dropout_6[0][0] |
output_activation (Activation) | (4) | 0 | output_layer[0][0] output_layer[1][0] output_layer[2][0] |