Convolutional neural networks (CNNs) are a type of deep learning algorithm that is particularly effective at recognizing patterns and features in images.

There are many variations of CNNs, including fully convolutional networks, residual networks, and region-based CNNs

CNNs are composed of multiple layers of artificial neural networks, with each layer processing the input data and passing it on to the next layer

The key feature of CNNs is the use of convolutional layers, which apply a set of filters to the input data to extract features

CNNs are commonly used for tasks such as image classification, object detection, and facial recognition

CNNs require large amounts of labeled training data in order to learn effectively

CNNs are computationally intensive, and require specialized hardware such as GPUs to run effectively.