Context Aggregation Networks (CAN) (25 points) We can also implement a simple CNN model with dilated convolutions. We can have a model with a large receptive field with the same spatial resolution in the hidden layers. See the network architecture in the Table 1. For your information, the dilated residual network 2 is a similar model for image classification. \begin{tabular}{|c|c|c|c|c|c|c|} \hline Operation & 33 conv & 33 conv & 33 conv & 33 conv & 33 conv & Avg pool \\ \hline Activation & LReLU & LReLU & LReLU & LReLU & LRelU & N/A \\ \hline Dilation & 1 & 2 & 4 & 8 & 1 & N/A \\ \hline Receptive field & 33 & 77 & 1515 & 3131 & 3333 & N/A \\ \hline Feature channels & 32 & 32 & 32 & 32 & 10 & 10 \\ \hline \end{tabular}