Input Image

(227 x 227 x 3)

Data Preprocessing

MinMax Normalization, Augmentation

Conv2D(8) -> ReLU -> BatchNorm -> Max Pool

Conv2D(16) -> ReLU -> BatchNorm -> Max Pool

Conv2D(32) -> ReLU -> BatchNorm -> Max Pool

Conv2D(64) -> ReLU -> BatchNorm -> Max Pool

Flatten Layers

Dense Layers -> Dropout

Model training

Model Evaluation

Final Output