Convolution layer

A convolution layer is a type of neural network layer primarily used in deep learning models for processing data with a grid-like topology, such as images. It applies a convolution operation to the input, passing the result to the next layer. This operation helps in detecting features such as edges and textures in the input data, making it highly effective for tasks like image and video recognition.