Convolution Encodes Locality
Explain how local receptive fields and parameter sharing make convolution useful for image tasks.
A convolutional layer is not just another layer. It bakes image structure into the model. Images have local structure: nearby pixels form edges, textures, corners, and small parts. CNNs exploit that structure with filters that scan local windows across the image. Local receptive fields A unit looks at a small patch, not the whole image. That keeps the model focused on spatial neighborhoods where image evidence actually lives. Parameter sharing The same filter is reused across positions. If a yellow spot matters on the left side of a leaf, the same spot likely matters on the right side too. Hierarchy…
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