Convolutional Neural Networks (CNNs) are a class of deep learning models designed specifically for tasks like image recognition and processing. They consist of multiple layers, including convolutional layers, which detect features such as edges, textures, and patterns within images, and pooling layers that reduce dimensionality while preserving important information.
CNNs are highly effective for analyzing visual data, making them widely used in applications like facial recognition, medical imaging, and object detection. Their architecture mimics the way the human visual system processes visual information, enabling them to identify complex patterns with remarkable accuracy.