Convolutional Neural Networks (CNNs) consist of convolutional layers that scan images for local patterns (edges, textures) using filters.
These filters are small windows that move across the image and respond to specific patterns.
After the convolutional layers, the information is passed on to further layers that perform classification.
CNNs are primarily known for image analysis, but they also have a place in the world of GenAI. Their ability to recognize and manipulate spatial patterns gives them immense possibilities in the field of image generation.
CNNs understand the structure of an image, recognize its various elements, and know how to connect them to create a new image.