In the figure depicted above, the input and kernel (or filter) of the convolutional layer are represented by 𝑿 and 𝒘, respectively. Notably, the size of the kernel is typically smaller than that of the input, resulting in partial connectivity between each output unit and the input units. This design choice significantly reduces the computational cost and enables the CNN to extract meaningful features from small sub-regions of the input.