A 4.3.9 Convolutional Neural Networks (CNNs)
A4.3.9 describes how Convolutional Neural Networks (CNNs) adaptively learn spatial hierarchies of features in images. Their basic architecture includes input, convolutional, activation, pooling, fully connected, and output layers. The number of layers, kernel size, stride, activation function, and loss function all affect how CNNs process data and classify images By the end of this lesson, students will be able to:...