What is: Dense Block?
Source | Densely Connected Convolutional Networks |
Year | 2000 |
Data Source | CC BY-SA - https://paperswithcode.com |
A Dense Block is a module used in convolutional neural networks that connects all layers (with matching feature-map sizes) directly with each other. It was originally proposed as part of the DenseNet architecture. To preserve the feed-forward nature, each layer obtains additional inputs from all preceding layers and passes on its own feature-maps to all subsequent layers. In contrast to ResNets, we never combine features through summation before they are passed into a layer; instead, we combine features by concatenating them. Hence, the layer has inputs, consisting of the feature-maps of all preceding convolutional blocks. Its own feature-maps are passed on to all subsequent layers. This introduces connections in an -layer network, instead of just , as in traditional architectures: "dense connectivity".