- Unets are useful when the size of your outputs is similar to that of the input. So, any kind of generative modeling such as segmentation or decrappification.
- They don’t make sense for classification problems.
- Unets have a downsampling and upsampling path. These parts are also called encoder and decoder respectively.
- A layer in a neural network is always an affine function, such as a matrix multiplication, followed by a non-linearity, such as a relu.