**Random Gaussian Blur** is an image data augmentation technique where we randomly blur the image using a Gaussian distribution.

Image Source: [Wikipedia](https://en.wikipedia.org/wiki/Gaussian_blur)

**PReLU-Net** is a type of convolutional neural network that utilises parameterized ReLUs for its activation function. It also uses a robust initialization scheme - afterwards known as [Kaiming Initialization](https://paperswithcode.com/method/he-initialization) - that accounts for non-linear activation functions.

PReLU-Net

Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

Random Gaussian Blur

A **Concatenated Skip Connection** is a type of skip connection that seeks to reuse features by concatenating them to new layers, allowing more information to be retained from previous layers of the network. This contrasts with say, residual connections, where element-wise summation is used instead to incorporate information from previous layers. This type of skip connection is prominently used in DenseNets (and also Inception networks), which the Figure to the right illustrates.

Year	2000
Data Source	CC BY-SA - https://paperswithcode.com