Question - Why do we use convolutions for images instead of using fully connected layers?
Answer -
Each convolution kernel in a CNN acts like its own feature detector and has a partially in-built translation in-variance. Using convolutions lets one preserve, encode and make use of the spatial information from the image, unlike fully connected layers that do not have any relative spatial information.