Dense Connections

2000년 도입 · 논문 29,235편에서 사용

Dense Connections, or Fully Connected Connections, are a type of layer in a deep neural network that use a linear operation where every input is connected to every output by a weight. This means there are $n\_{\text{inputs}}*n\_{\text{outputs}}$ parameters, which can lead to a lot of parameters for a sizeable network. $$h\_{l} = g\left(\textbf{W}^{T}h\_{l-1}\right)$$ where $g$ is an activation function. Image Source: Deep Learning by Goodfellow, Bengio and Courville