A Convolutional Neural Network (CNN) is a type of deep learning model specifically designed for image processing tasks. It uses convolutional layers to scan input images and detect local features, such as edges and textures. Vision Transformers (ViT) are a more recent approach that applies the transformer architecture, originally designed for natural language processing tasks, to image classification. ViT divides images into smaller patches and processes them in parallel using self-attention mechanisms, which can lead to improved performance and efficiency compared to CNNs.