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Figure 1: CNN Architecture

A typical CNN architecture showing the flow from input image through convolutional layers, pooling layers, and fully connected layers to the final output.

Figure 2: Convolution Operation

Step-by-step visualization of the convolution operation showing the sliding window, element-wise multiplication, and summation to produce the output feature map.

Figure 3: Pooling Operations

Comparison of max pooling and average pooling. Max pooling selects the maximum value, while average pooling computes the mean of values in each window.