Convolution Operation

The convolution operation slides a small learnable filter (kernel) across an input image, computing dot products at each spatial position. This produces a feature map that highlights where specific patterns like edges, textures, or shapes appear in the input.

Unlike fully connected layers, convolutions exploit spatial locality and weight sharing — dramatically reducing parameters while preserving the spatial structure of visual data.