Convolutional neural networks (CNNs) are a type of deep learning model commonly used in computer vision tasks such as image recognition and classification. CNNs are designed to automatically learn and extract hierarchical features from input data, through a series of convolutional and pooling layers. These layers help the network identify patterns and structures within the data, making them well-suited for tasks like object detection and image segmentation. CNNs have been shown to achieve state-of-the-art performance on various visual recognition tasks and are widely used in industry and research.