What is a convolutional neural network (CNN)?

A Convolutional Neural Network (CNN) is a deep learning architecture designed for grid-like data such as images. It uses convolutional layers that apply learned filters across the input, detecting local patterns like edges and textures. Pooling layers downsample spatial dimensions, reducing computation and providing translation invariance. Multiple conv+pool blocks are followed by fully connected layers for classification. CNNs automatically learn hierarchical features: edges → textures → parts → objects. Landmark architectures: AlexNet, VGG, ResNet, InceptionNet, EfficientNet.