Convolutional Neural Networks

Luca Antiga 1. Convolutional Neural Networks (CNNs) are a powerful tool for deep learning, capable of extracting meaningful features from complex data. 2. CNNs are especially suited for image recognition tasks, as they are designed to work with 2-dimensional arrays of data. 3. CNNs are comprised of a series of convolutional layers that filter input data to create feature maps. 4. A pooling layer is then applied to reduce the size of the feature maps, making it easier to process. 5. Fully connected layers are then used to make predictions from the feature maps. 6. CNNs are also capable of learning from smaller datasets than other networks, making them attractive for applications with limited data. 7. Finally, CNNs are capable of operating at high speeds, making them ideal for real-time applications.