Python Deep Learning - Second Edition

DenseNets

DenseNet stands for Densely-Connected Convolutional Networks. It tries to alleviate the vanishing gradient problem and improve feature propagation, while reducing the number of network parameters. We've already seen how ResNets introduce residual blocks with skip connections to solve this. DenseNets take some inspiration from this idea and introduce dense blocks. A dense block consists of sequential convolutional layers, where any layer has a direct connection to all subsequent layers:

A dense block: The dimensionality-reduction layers (dashed lines) are part of the DenseNet-B architecture, while the original DenseNet doesn't have ...