A convolutional neural network (CNN) is a type of machine learning architecture that expertly handles image-recognition and classification applications, including facial recognition, object detection, and medical diagnosis. CNNs learn from data through layers of nodes and filters that process images in a hierarchical manner, identifying features such as colors, edges, and patterns. By utilizing parameter sharing and downsampling, CNNs can improve efficiency and reduce overfitting, making them particularly well-suited for large-scale image processing tasks. The use of CNNs has led to significant advancements in the field of computer vision, enabling applications such as ecommerce visual search and medical diagnosis, and has improved accuracy in image recognition and classification.