CategoryHierarchies.com

Convolutional Neural Networks, often abbreviated as CNNs, are a type of artificial neural network commonly used in computer vision tasks. They are designed to automatically and adaptively learn spatial hierarchies of features from images, making them highly effective at recognizing patterns and objects within visual data. This is achieved through the use of convolutional layers, which apply a series of filters or kernels to the input image to extract low-level features like edges and textures, followed by pooling layers that reduce the spatial dimensions while retaining important information. As the network deepens, higher-level abstractions are learned, enabling CNNs to detect complex patterns and objects with high accuracy. In this hierarchy, Convolutional Neural Networks fall under Computer Vision and contribute significantly to Artificial Intelligence Algorithms within the broader field of Artificial Intelligence and Technology.