Number of Parameters: ~11.7M (ResNet-18 pretrained model)
Output: Multi-class classification (9 classes)
Model Description
This model uses ResNet-18, a well-known deep residual network, pre-trained on ImageNet. The model is fine-tuned by replacing the fully connected layer to accommodate multi-class classification for skin cancer detection. Only the fully connected layer is trainable, while the convolutional layers of the ResNet model are frozen to retain pretrained features.
The final model performs multi-class classification with 9 output classes corresponding to different skin cancer types.
