What is a convolution operation in CNNs?

Convolution applies a filter over input data to extract local features like edges and textures.

Convolution involves sliding a kernel (filter) over an input image and computing dot products at each position. This produces feature maps that highlight specific patterns. Each filter learns to detect a different feature during training, enabling hierarchical feature extraction.