The Convolution Operation
A fully-connected layer applied directly to a 224×224 RGB image would need over 150,000 input weights per single output unit — and that's before considering how many units a layer needs. Convolution replaced that with a small, shared filter slid across the image, cutting parameters by orders of magnitude while adding a property fully-connected layers structurally lack: the same filter finds the same pattern no matter where in the image it appears.