Capsule Networks

Capsule Networks are a type of artificial neural network designed to improve the way deep learning models recognize patterns in visual data. They utilize capsules, which are small groups of neurons that work together to identify specific features and their spatial relationships in an image. This architecture aims to overcome limitations of traditional convolutional neural networks (CNNs), particularly in handling variations in viewpoint and orientation. Capsule Networks are particularly effective in tasks such as image classification, object detection, and image segmentation, where understanding the hierarchical relationships between features is crucial.