  Pixel-wise street segmentation of photographs taken from a drivers
perspective is important for self-driving cars and can also support other
object recognition tasks. A framework called SST was developed to examine the
accuracy and execution time of different neural networks. The best neural
network achieved an $F_1$-score of 89.5% with a simple feedforward neural
network which trained to solve a regression task.
