Convolutional Neural Networks

Convolutional Neural Networks (CNNs) are a class of deep learning algorithms specifically designed for processing structured grid data, such as images. They utilize convolutional layers to automatically and adaptively learn spatial hierarchies of features from input images. CNNs are characterized by their ability to reduce the number of parameters in the model while maintaining high accuracy, making them efficient for tasks such as image recognition, object detection, and image segmentation. Common use cases include facial recognition systems, medical image analysis, and self-driving car technology, where understanding visual data is crucial.