Explain why the model’s reliance on convolution and pooling may be limiting its ability to generalize to new image classes. Propose an alternative architecture that balances the strengths of these operations while improving generalization performance.

The model’s over-reliance on convolution and pooling as an ‘infinitely strong prior’ limits its ability to generalize to new image classes. To improve generalization, we can add more diverse layers, such as fully connected or residual connections, to provide additional paths for feature extraction and reduce the model’s reliance on convolutional networks.