Convolutional Networks: Motivation & Ideas

This lecture covers the motivation and ideas behind convolutional networks, focusing on weight sharing, receptive fields, and post-activation. It explains the concept of convolutional layers, fully connected layers, and pooling layers, including max-pooling and average-pooling. The lecture also discusses the shift stride, index of the channel, and the role of non-linear functions in convolutional networks.