Convolutional Neural Networks

CNNs are deep learning architectures that use convolution operations to automatically learn hierarchical feature representations. They employ shared weights, pooling layers, and local connectivity patterns to efficiently handle spatial hierarchies of features. They typically consist of convolutional layers for feature extraction, pooling layers for dimensionality reduction, and fully connected layers for classification. CNNs leverage parameter sharing and local connectivity to efficiently process visual data.

Image recognition video analysis medical imaging facial recognition systems